myScience

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    "title": "Postdoctorant au Laboratoire de Musicologie Numérique et Cognitive, EPFL Lausanne",
    "description": "Nouvelle opportunite : Postdoctorant au Laboratoire de Musicologie Numérique et Cognitive, EPFL Lausanne chez myScience (Lausanne).\n\nPostdoc au Laboratoire de Musicologie Digitale et Cognitive de l'EPFL. Rejoignez une équipe proactif et interdisciplinaire à Lausanne.\nTâches\n•\nExplorer la structure musicale et l'esprit musical par des modèles avancés.\n•\nConduire des recherches empiriques avec des compétences analytiques solides.\n•\nCollaborer au sein d'une équipe diversifiée et passionnée par la musique.\nCompétences\n•\nDoctorat en musicologie, informatique, psychologie ou domaine connexe requis.\n•\nCompétences en programmation et en statistiques nécessaires.\n•\nAnglais courant et esprit d'équipe appréciés.\nPostdoctorant au Laboratoire de Musicologie Numérique et Cognitive, EPFL Lausanne\nÉcole polytechnique fédérale de Lausanne, EPFL\nLieu de travail\nLausanne\n-\nRégion du lac Léman\n-\nSuisse\nCatégorie\nMathématiques\n|\nGestion de la recherche\nRole\nChercheur senior / Postdoctorant\nPublié\n12 février 2026\nL’EPFL, l’École polytechnique fédérale de Lausanne, est l’un des campus universitaires les plus dynamiques d’Europe et figure parmi les 20 meilleures universités mondiales. L’EPFL emploie plus de 6 500 personnes soutenant les trois missions principales de l’institution : l’enseignement, la recherche et l’innovation. Le campus de l’EPFL offre un environnement de profession exceptionnel au cœur d’une communauté de plus de 18 500 personnes, dont plus de 14 000 étudiants et 4 000 chercheurs issus de plus de 120 pays différents.\nOpportunite de postdoctorant (100%) au Laboratoire de Musicologie Numérique et Cognitive, EPFL Lausanne\nNous recherchons un chercheur partageant notre fascination pour la structure musicale et l’esprit musical, prêt à l’aborder à l’aide de modélisation computationnelle avancée, modélisation mathématique ou psychologie expérimentale.\nProfil\nNous valorisons la collaboration interdisciplinaire. Vous devez être titulaire d’un doctorat en musicologie, informatique, sciences cognitives, psychologie, mathématiques ou dans un domaine connexe. Bien que vous apportiez votre propre spécialisation, vous devez posséder :\n•\nDe solides compétences analytiques et une expérience avérée dans la planification et la conduite de recherches empiriques.\n•\nUne maîtrise de la programmation et des statistiques/sciences des données.\n•\nUne véritable passion pour la musique et une bonne compréhension musicale.\n•\nUn anglais courant et un esprit d’équipe collaboratif.\nNous offrons\n•\nEst a la recherche de de classe mondiale : L’EPFL est une institution internationale de premier plan. Vous rejoindrez une équipe jeune et dynamique intégrant diverses disciplines.\n•\nAvantages sociaux : Les postdoctorants à l’EPFL sont des employés réguliers à plein temps bénéficiant d’excellents avantages sociaux et de salaires compétitifs.\n•\nÉvolution de carrière : Opportunités d’acquérir de l’expérience en enseignement, mentorat et supervision dans un écosystème de soutien.\n•\nVie à Lausanne : Située sur les rives du lac Léman avec vue sur les Alpes, Lausanne offre un cadre pittoresque avec des événements culturels dynamiques et des activités de plein air.\nInformations\nSeules les candidatures soumises via la plateforme en ligne seront prises en compte. Vous devez fournir :\n•\nUne lettre de motivation\n•\nUn CV avec une liste de publications\n•\nLes coordonnées de 2 références\nLes femmes sont vivement encouragées à postuler.\nPour toute information complémentaire, veuillez contacter : martin.rohrmeier@\nepfl.ch\nL’examen des candidatures commence le 2 mars 2026 et se poursuit jusqu’à ce que le offre d'emploi soit pourvu.\nNotre projet de recherche est financé par le Fonds national suisse de la est a la recherche de scientifique (FNS).\nDate de début du contrat : Flexible (été 2026 préféré)\nTaux d’activité : 100%\nType de contrat : CDD\nDurée : Un an, renouvelable\nRéférence : 2065\nPlus d’informations\nDans votre candidature, veuillez mentionner\nmyScience.ch\net référencer\nJobID69244\n.\n\nNe laissez pas passer cette offre -- postulez maintenant.",
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    "@id": "https://ch-jobs.com/job/senior-lecturer-type-1-mer1-in-statistics-applied-to-movement-and-sports-sciences-80-2#jobposting",
    "title": "Senior Lecturer type 1 (MER1) in statistics applied to movement and sports sciences (80%)",
    "description": "Vous cherchez un emploi de Senior Lecturer type 1 (MER1) in statistics applied to movement and sports sciences (80%) a Lausanne ? myScience recrute.\n\nUNIL recherche un Senior Lecturer en statistiques appliquées aux sciences du sport. Ce role offre un environnement dynamique et multicultural.\nTâches\n•\nEnseigner et superviser des mémoires de maîtrise et des thèses.\n•\nMener des recherches en statistiques appliquées au sport.\n•\nParticiper aux tâches administratives liées au poste.\nCompétences\n•\nDoctorat en sciences du sport ou statistiques requis.\n•\nExpérience d'enseignement académique nécessaire.\n•\nMaîtrise du français exigée.\nSenior Lecturer type 1 (MER1) in statistics applied to movement and sports sciences\nUNIL - Faculté des SSPDécanat SSP\nWorkplace\nLausanne-Dorigny\n- Lake Geneva region - Switzerland\nCategory\nEducation | Sport\nPosition\nLecturer\nDuration\n6 years, renewable\nOccupation rate\n80%\nJob Start\n01.02.2027 or 01.08.2027 or to be agreed\nPublished\n14 May 2026\nClosing Date\n15 June 2026\nIntroduction\nUNIL is a leading international teaching and research institution, with over 5,000 employees and 17,000 students split between its Dorigny campus, CHUV and Epalinges. As an employer, UNIL encourages excellence, individual recognition and responsibility.\nunil.ch/work\nPresentation\nIn order to complete our team, the Faculty of Social and Political Sciences and the Institute of Sports Sciences of the University of Lausanne (ISSUL) wishes to expand its team by recruting a :\nSenior Lecturer type 1 (MER1)\nin\nstatistics applied to movement and sports sciences\nInformation\nExpected start date in position :\n01.02.2027 or 01.08.2027 or to be agreed\nContract length : 6 years, renewable\nActivity rate : 80%\nWorkplace : University of Lausanne, Dorigny, 1015 Lausanne\nDescription\nYour responsibilities\nIn your functions, you will have to :\nTeaching (36%)\nFive hours a week of teaching throughout the year in French. Additionaly supervision of Master’s dissertations and PhD theses.\nResearch (40%)\nThe post-holder will pursue their own research in statistics applied to sport and physical education. They will be expected to produce high-quality international publications. It is expected that the post-holder will be affiliated to one of the Faculty’s research centres.\nThey will also seek external funding, in particular from the Swiss National Science Foundation (SNSF).\nThe post-holder will participate in the statistical consultation and data analysis service provided to staff and students in the Institute of Sports Sciences (ISSUL).\nAdministrative responsibilities (4%)\nIn accordance with statutory requirements and in the name of collegiality, the post-holder will take on any administrative tasks that may be assigned to them by the Institute, including administrative management tasks associated with their post.\nThe post is located in the Institute of Sports Sciences and the Faculty of Social and Political Sciences.\nRemuneration\nPursuant to Rectorate Directive 1.24 on setting the initial salary of teaching staff at the University of Lausanne , the initial salary is set according to the Senior Lecturer type 1 (MER1) salary scale , regardless of age and prior professional background.\nRequirements\nYour qualifications\nIn order to complete our team, we are looking for someone with the following skills :\n•\nPhD in sports sciences, statistics or equivalent qualification\n•\nAcademic teaching experience\n•\nProven research record in the field of statistics applied to sport and physical education\n•\nGood links with research networks\n•\nVery high proficiency in French\nYour application\nDeadline :\n15th June 2026\nCandidates are invited to submit their application via the online platform including:\n•\na covering letter\n•\na CV,\nincluding a publications list\n•\na copy of their diplomas and qualifications\n•\nfive main publications in PDF format.\nOnly applications submitted via the online system will be considered.\nReferences\n: a maximum of three names with e-mail addresses is sufficient. There is no need to contact them at this stage of the application process; we will do so if necessary.\nWe thank you for your understanding.\nWe offer\nWhat the position offers you\nWe offer a nice working place in a multicultural, diverse and dynamic academic environment. Opportunities for professional training, a lot of activities and other benefits to discover.\nunil.ch/work\nAdditional information\nUNIL is committed to:\n•\nequality, diversity and inclusion within its community;\n•\nensuring an open and respectful environment that is conducive to personal development;\n•\noffering working conditions that facilitate work-life balance;\n•\nsupporting early career researchers.\nIn order to increase the number of female teachers, applications from women are particularly encouraged.\nunil.ch/equality\nunil.ch/families\nunil.ch/graduatecampus\nContact and Address\nContact for further information\nFurther information can be obtained from : recrute",
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    "title": "Ingénieurs en recherche IA - Initiative Apertus",
    "description": "myScience ouvre un poste de Ingénieurs en recherche IA - Initiative Apertus a Lausanne.\n\nRejoignez l'EPFL comme Ingénieur en IA pour l'Initiative Apertus. Une opportunité unique au sein d'un environnement de cherche dynamique.\nTâches\n•\nDévelopper des modèles d'IA ouverts et transparent.\n•\nCollaborer avec des chercheurs de renommée mondiale.\n•\nContribuer à des projets d'impact mondial en IA.\nCompétences\n•\nMaster en informatique ou domaine connexe exigé.\n•\nCompétences avancées en programmation Python requises.\n•\nExpérience en optimisation de l'IA souhaitée.\nIngénieurs en recherche IA - Initiative Apertus\nÉcole polytechnique fédérale de Lausanne, EPFL\nLieu de travail\nLausanne\n-\nRégion du lac Léman\n-\nSuisse\nCatégorie\nInformatique\n|\nInnovation\nOuverture\nIngénieur / Technicien\nPublié\n27 avril 2026\nL’EPFL, l’École polytechnique fédérale de Lausanne, est l’un des campus universitaires les plus dynamiques d’Europe et figure parmi les 20 meilleures universités mondiales. L’EPFL emploie plus de 6 500 personnes soutenant les trois missions principales de l’institution : l’enseignement, la est a la recherche de et l’innovation. Le campus de l’EPFL offre un environnement de travail exceptionnel au cœur d’une communauté de plus de 18 500 personnes, comprenant plus de 14 000 étudiants et 4 000 chercheurs issus de plus de 120 pays différents.\nIntroduction\nL’Initiative Apertus, un effort conjoint entre l’EPFL et l’ETH Zürich, recherche des ingénieurs talentueux pour rejoindre notre équipe développant la prochaine génération de modèles fondamentaux ouverts. En travaillant avec le superordinateur public d’IA le plus puissant au monde (Alps), nous visons à créer des LLM ouverts et transparents ainsi que des modèles d’IA multimodaux qui bénéficient à la société suisse tout en maintenant la souveraineté technologique.\nPrincipales tâches et responsabilités\nNous recrutons des ingénieurs logiciels en recrute IA ayant une expertise dans un ou plusieurs des domaines suivants :\no Formation et optimisation distribuées en IA\no Curation de données (texte et multimodal)\no Évaluation et benchmarking de modèles\no Systèmes d’inférence et déploiement\no Raisonnement\no Modèles d’IA multimodaux\nProfil\n•\nMaster en informatique, science des données, IA ou domaine connexe (les candidats exceptionnels titulaires d’un bachelor seront également considérés)\n•\nExpérience en IA et architectures de réseaux neuronaux\n•\nSolides compétences en programmation Python et connaissance de PyTorch ou de frameworks ML similaires\n•\nExpérience des pratiques de développement logiciel, y compris les systèmes de contrôle de version, le débogage, les tests et le déploiement.\n•\nExcellentes capacités de résolution de problèmes et fortes compétences analytiques.\n•\nCapacité à travailler efficacement en équipe ainsi qu’en autonomie.\nVeuillez noter que seules les candidatures répondant aux critères de l’annonce seront prises en compte.\nNous offrons\n•\nUn environnement académique stimulant dans l’une des universités techniques les plus prestigieuses au monde\n•\nL’opportunité de travailler avec une infrastructure de supercalcul à la pointe et une recherche en IA de pointe\n•\nCollaboration avec des chercheurs et ingénieurs de premier plan de l’EPFL, de l’ETH Zurich, du CSCS et d’autres institutions suisses\n•\nModalités de travail flexibles, y compris des options de télétravail\n•\nOpportunités de développement professionnel, y compris la participation à des conférences et des formations spécialisées\n•\nLa chance de contribuer à des projets open source à impact mondial\n•\nAccès à l’écosystème académique suisse plus large et aux partenariats industriels\n•\nFaire partie du développement souverain de l’IA en Suisse, en travaillant sur une technologie d’importance nationale\nInformations\nDate de début du contrat : dès que possible\nTaux d’activité min : 80.00\nTaux d’activité max : 100.00\nType de contrat : CDD\nDurée : 1 an, renouvelable\nRéférence : 2192\nPlus d’informations\nDans votre candidature, veuillez mentionner\nmyScience.ch\net référencer\nJobID69729\n.\n\nRejoignez myScience et donnez un nouvel elan a votre carriere.",
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    "@id": "https://ch-jobs.com/job/ingenieur-de-recherche-en-mesures-atmospheriques-en-environnements-extremes-2#jobposting",
    "title": "Ingénieur de recherche en mesures atmosphériques en environnements extrêmes",
    "description": "myScience recrute un(e) Ingénieur de recherche en mesures atmosphériques en environnements extrêmes a Lausanne.\n\nIngénieur de cherche en mesures atmosphériques à l'EPFL.\nTâches\n•\nDévelopper et maintenir le système helikite pour des mesures.\n•\nConcevoir des expériences et contribuer à de nouveaux besoins.\n•\nParticiper aux campagnes sur le terrain et soutenir la logistique.\nCompétences\n•\nDiplôme en ingénierie avec expérience en mécatronique.\n•\nCompétences en conception de circuits et systèmes embarqués.\n•\nExpérience en gestion de projets et emploi en équipe.\nIngénieur de recherche en mesures atmosphériques en environnements extrêmes\nÉcole polytechnique fédérale de Lausanne, EPFL\nLieu de emploi\nLausanne\n-\nRégion du lac Léman\n-\nSuisse\nCatégorie\nEnvironnement\n|\nSciences de la Terre\nPoste\nIngénieur / Technicien\nPublié\n29 avril 2026\nL’EPFL, l’École polytechnique fédérale de Lausanne, est l’un des campus universitaires les plus dynamiques d’Europe et figure parmi les 20 meilleures universités mondiales. L’EPFL emploie plus de 6 500 personnes soutenant les trois missions principales de l’institution : l’enseignement, la est a la recherche de et l’innovation. Le campus de l’EPFL offre un environnement de travail exceptionnel au cœur d’une communauté de plus de 18 500 personnes, dont plus de 14 000 étudiants et 4 000 chercheurs issus de plus de 120 pays différents.\nMission\nLe Laboratoire de cherche sur les environnements extrêmes (EERL) recherche un ingénieur de recherche pour soutenir et améliorer nos mesures sur le terrain et en laboratoire des aérosols atmosphériques, des gaz traces et des nuages. L’EERL mène plusieurs projets dans l’Arctique et l’Antarctique, incluant la participation à de grandes initiatives internationales telles que Tara Polar Station et Antarctica InSync. Plus précisément, nous nous concentrons sur les mesures verticales, notre helikite EERL étant la plateforme principale. Comme charge utile, nous déployons à la fois des instruments commerciaux et nos propres développements. Notre nouveau système d’helikite (AVATAR) est presque entièrement automatisé, permettant à un seul opérateur de gérer le système dans des conditions difficiles. Nous prévoyons de le développer davantage pour un déploiement à grande échelle.\nLe candidat retenu sera intéressé par le développement des systèmes existants ainsi que par la création de nouveaux pour repousser les limites de nos capacités d’observation. Il aura également un intérêt réel pour les sciences atmosphériques et des aérosols, ainsi que pour les régions polaires.\nL’EERL fait partie du nouveau Centre de recherche environnementale alpine et polaire (ALPOLE) de l’EPFL sur le campus de Sion.\nPour postuler via la plateforme de recrutement de l’EPFL, veuillez soumettre une lettre de motivation incluant vos intérêts et qualifications, un CV et - le cas échéant - une liste de publications, ainsi que les contacts de trois référents.\nLe poste sera accordé initialement pour deux ans avec une vision à long terme. La date de début souhaitée est le 15 juillet 2026 ou dès que possible après cette date.\nPrincipales tâches et responsabilités\n•\nDévelopper et maintenir le système d’helikite (treuil, ordinateur de bord, système de communication/\ncontrôle, intégration des instruments dans la charge utile) et d’autres systèmes de laboratoire sur mesure\n•\nObtenir les autorisations de vol\n•\nConcevoir des expériences et contribuer avec ses propres idées aux nouveaux besoins observationnels et instrumentaux qui émergent\n•\nSoutenir les chercheurs de l’EERL dans la maintenance et la réparation des instruments\n•\nSoutenir la logistique sur le terrain\n•\nParticiper aux campagnes sur le terrain\n•\nMaintenir les normes de santé et sécurité en laboratoire\n•\nDocumenter le travail et les systèmes\n•\nContribution générale aux activités de l’EERL.\n•\nParticiper à l’encadrement des étudiants.\n•\nPromouvoir la recherche polaire et son impact auprès du public.\nProfil\n•\nMaster en ingénierie avec expérience en génie électrique et mécanique, mécatronique et physique appliquée\n•\nCompétences en conception de circuits analogiques & numériques, conception de PCB, systèmes embarqués (ARM, Arduino, STM32), bases en traitement du signal\n•\nExpérience en programmation (par exemple, python, Matlab) et gestion/visualisation de données\n•\nExpérience en construction de prototypes\n•\nExpérience en travail de laboratoire et réparation d’instruments\n•\nExpérience en gestion de projet\n•\nExpérience en travail sur le terrain est un atout\n•\nBonnes compétences interpersonnelles, esprit d’équipe.\n•\nBonne maîtrise de l’anglais (écrit et parlé).\nNous offrons\n•\nUn groupe de recherche dynamique, interdisciplinaire et jeune.\n•\nUne institution académique vibrante, visible à l’international e",
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    "@id": "https://ch-jobs.com/job/postdoctoral-researcher-in-multimodal-human-sensing-and-advanced-behavioral-data-analysis-1#jobposting",
    "title": "Postdoctoral Researcher in Multimodal Human Sensing and Advanced Behavioral Data Analysis",
    "description": "myScience est a la recherche d'un(e) Postdoctoral Researcher in Multimodal Human Sensing and Advanced Behavioral Data Analysis pour son site de Lausanne.\n\nLe poste de chercheur postdoctoral à l'EPFL offre un cadre de travail dynamique. Rejoignez une équipe innovante dédiée à la recherche sur le comportement humain.\nTâches\n•\nDévelopper des tâches comportementales en réalité virtuelle immersive.\n•\nIntégrer des systèmes de données physiologiques et comportementales.\n•\nAnalyser des données multimodales pour étudier la motivation humaine.\nCompétences\n•\nDoctorat en ingénierie biomédicale, neurosciences ou domaines connexes.\n•\nCompétences en programmation, idéalement en Python ou R.\n•\nExpérience en analyse de données complexes et multimodales.\nPostdoctoral Researcher in Multimodal Human Sensing and Advanced Behavioral Data Analysis\nSwiss Federal Institute of Technology Lausanne, EPFL\nWorkplace\nLausanne\n- Lake Geneva region - Switzerland\nCategory\nComputer Science | Health\nPosition\nSenior Scientist / Postdoc\nPublished\n21 May 2026\nEPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries.\nPostdoctoral Researcher in Multimodal Human Sensing and Advanced Behavioral Data Analysis\nMission\nSwiss National Science Foundation (SNSF)-funded project on human motivation, stress physiology, immersive behavioral testing, and multimodal data analysis\nThe Laboratory of Behavioral Genetics at EPFL, led by Prof. Carmen Sandi, is seeking an outstanding postdoctoral researcher with a strong technical and quantitative profile to join a SNSF-funded project investigating human motivation and stress responsiveness.\nThe project will develop and validate individually calibrated behavioral tasks in immersive virtual reality (VR) to quantify effort-based motivation, vigor, persistence and goal-directed versus habitual control. It will then test how acute stress alters these processes, combining behavioral performance, physiological monitoring, movement-based phenotyping, and advanced statistical and computational analyses.\nThis position is part of a broader two-position recruitment linked to the same SNSF-funded project. The call is for the position focused on\nmultimodal sensing, experimental systems, physiological and movement data, and advanced behavioral data analysis\n. A second, complementary position will focus more specifically on clinical and implementation aspects of the project.\nAlthough the project uses virtual reality as an experimental platform, prior VR background is not necessarily required. We are\nparticularly interested in candidates with strong expertise in\nexperimental systems, physiological sensing, signal processing, human movement analysis, computational neuroscience, biomedical engineering, data science, and/or advanced quantitative behavioral research.\nThe position is funded for\nthree years\n. In line with standard EPFL procedures, the contract is issued on a\none-year basis and renewable annually\n, subject to satisfactory progress and institutional regulations.\nProject background\nUnderstanding human motivation requires methods that go beyond questionnaires and simplified computer-based tasks. This project aims to develop more naturalistic, yet highly controlled, behavioral assays in which participants make effort-based decisions and perform calibrated actions while physiological and movement data are continuously recorded.\nParticipants will complete immersive behavioral tasks designed to measure how they choose, initiate action, sustain effort, adapt to changing contingencies and respond to acute stress. The project will collect synchronized streams of trial-level behavioral data, head/hand/body positioning, movement trajectories, timing variables, ECG-derived heart rate and heart-rate variability, electrodermal activity, respiration, salivary cortisol and questionnaire-\nbased individual-\ndifference measures.\nA central aim is to identify robust behavioral and physiological signatures of motivation and stress responsiveness, including individual profiles of response. The successful candidate will play a key role in ensuring that these complex data streams are acquired, synchronized, quality-controlled, modeled and interpreted with the highest level of technical and analytical rigor.\nMain responsibilities\nThe postdoctoral researcher will lead the technical and quantitative core of the project. Responsibilities will include:\n•\nDeveloping, implementing, optimizing and troubleshooting immersive behavioral tasks in close interaction with the PI and lab",
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    "title": "PhD Candidate in Applied ML and NLP",
    "description": "myScience recrute un(e) PhD Candidate in Applied ML and NLP a Zurich.\n\nETH Zurich recherche un candidat au doctorat en ML et NLP. Rejoignez un environnement innovant et impactant.\nTâches\n•\nDévelopper des systèmes IA pour le traitement juridique.\n•\nConstruire des prototypes de qualité pour des déploiements pilotes.\n•\nConduire des évaluations systématiques de la performance des modèles.\nCompétences\n•\nMaster en informatique, data science ou domaine connexe exigé.\n•\nSolides compétences en ML et NLP nécessaires.\n•\nExpérience en déploiement d'applications souhaitée.\nPhD Candidate in Applied ML and NLP\nEidgenossische Technische Hochschule Zürich, ETHZ\nWorkplace\nZurich\n- Zurich region - Switzerland\nCategory\nInnovation | Computer Science\nPosition\nJunior Researcher / PhD Position\nPublished\n16 April 2026\n100%, Zurich, fixed-term\nAs part of the SNSF-funded project ’Responsible AI for the Swiss Judiciary’, we work on real-world applications of artificial intelligence for the Swiss judiciary in close collaboration with courts and partners across Switzerland. We are looking for a PhD candidate in Applied ML and NLP. This doctoral position is part of the SNSF-funded project ’Responsible AI for the Swiss Judiciary’ at ETH Zurich. The project develops and evaluates AI-based prototypes to support judicial decision-making, with a focus on real-world applicability. It combines machine learning, legal applications, and empirical evaluation in collaboration with judicial partners. The project offers a unique opportunity to work on real-world, high-stakes AI systems in collaboration with courts, combining cutting-edge AI research with impactful societal applications.\nJob description\nThe doctoral researcher will focus on the development and evaluation of AI-based research prototypes for legal applications, with a strong emphasis on technical implementation and real-world deployment.\nCore responsibilities include:\n•\nDeveloping and implementing AI systems for legal text processing and decision support (e.g., LLMs, retrieval-augmented generation, agentic systems)\n•\nBuilding production-\nquality prototypes suitable for pilot deployment in judicial settings, including robust retrieval systems, LLM pipelines, and evaluation infrastructure\n•\nDesigning and running systematic evaluations of model performance, robustness, and reliability\n•\nBuilding datasets, benchmarks, and pipelines for legal AI applications\n•\nImproving model architectures, prompting strategies, and retrieval systems for high-stakes environments\n•\nConducting pilot evaluations with judicial partners to study how AI tools perform in real decision-making workflows, and translating findings into technical improvements (e.g., new embedding methods, agent architectures, prompting strategies)\n•\nPublishing research results in leading venues in artificial intelligence and computational social science\n•\nThe position is designed for a cumulative PhD with a strong methodological and technical focus\n•\nOur offices are located in downtown Zurich, and the working languages are German and English\nProfile\nWe are looking for candidates who combine strong ML/NLP fundamentals with hands-on engineering skills; someone who understands how models work under the hood and can also build reliable, deployable systems. You:\n•\nMust hold a master’s degree in computer science, data science, or a closely related field\n•\nHave strong analytical and problem-solving skills\n•\nAre able to work independently and take ownership of technical components\n•\nAre interested in applying AI methods to real-world, high-stakes domains\n•\nAre motivated to work with legal stakeholders from the Swiss judiciary\n•\nHave expertise with large language models, information retrieval, evaluation of ML systems, and deploying applications; this is highly desirable\n•\nHave an excellent command of English; German language skills are a plus\nWorkplace\nWe offer\n•\nYour job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society\n•\nYou can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits\nWorking, teaching and research at ETH Zurich\nWe value diversity and sustainability\nIn line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us - we are consistently working towards a climate-neutral future .\nCurious? So are we.\nWe look forward to receiving your online application with the following documents:",
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    "title": "PhD Position: Agro-Economic Analysis of Legume-Cereal Mixtures (PhenoMix project)",
    "description": "myScience recrute un(e) PhD Position: Agro-Economic Analysis of Legume-Cereal Mixtures (PhenoMix project) a Zurich.\n\nETH Zurich propose un position de doctorat en analyse agro-économique.\nTâches\n•\nPlanifier et évaluer des expériences de terrain et de laboratoire.\n•\nRéaliser des analyses statistiques, y compris des approches basées sur l'IA.\n•\nPrésenter les résultats lors d'événements nationaux et internationaux.\nCompétences\n•\nUn diplôme de MSc en sciences agricoles ou dans un domaine connexe.\n•\nExpérience en planification d'expériences et analyses statistiques.\n•\nExcellentes compétences en communication écrite et orale.\nPhD Position: Agro-Economic Analysis of Legume-Cereal Mixtures (PhenoMix project)\nEidgenossische Technische Hochschule Zürich, ETHZ\nWorkplace\nZurich\n- Zurich region - Switzerland\nCategory\nAgronomy & Food Science | Environment\nPosition\nJunior Researcher / PhD Position\nPublished\n21 April 2026\nPhD Position: Agro-Economic Analysis of Legume-Cereal Mixtures (PhenoMix project)\n100%, Zurich, fixed-term\nThis doctoral student position is part of the project ’ PhenoMix: Multidimensional field phenotyping of crop mixtures ’, supported by the Swiss National Science Foundation. The position is hosted by the Crop Science group; a vibrant and interdisciplinary working group in the Institute of Agricultural Sciences at the Department of Environmental Systems Science at ETH Zurich. Our group’s phenotyping research focuses on the development of methods and models to determine traits of relevance for crop breeding and variety testing. The Agroscope research group Extension Arable Crops (Competence division Plants and Plant Products) develops ecological solutions for disease, pest and weed control and evaluates crop varieties for their suitability under Swiss conditions. It takes a holistic approach to create sustainable, cost-efficient, and climate-resilient arable farming systems.Please enter text here\nProject background\nPhenoMix\nis a joint project of four research groups at ETH Zurich, the Swiss Data Science Center and Agroscope. The overall objective of\nPhenoMix\nis to test the hypothesis that current high throughput field phenotyping technology in combination with plant physiological and ecosystem service assessments can provide a breakthrough to determine genotypes that can be successfully combined in agroecologically beneficial legume-cereal mixtures. Different varieties of legumes (peas, lentils) and cereals (wheat, oats, barley) will be grown in pure stands and in mixtures on the field phenotyping platform FIP of the Crop Science group, on a neighbouring experimental field and on farmer’s fields. The\nPhenoMix\nWork Packages address phenotyping, plant ecophysiology, data science, and agronomic-economic performance with four doctoral students, two postdocs and several technicians assigned to those work packages. The Agro-Economic doctoral student will establish and monitor on-site and on-farm field experiments investigating several lentil-cereal mixtures by assessing various ecosystem services.\nJob description\nThis doctoral project will form an important cornerstone in the mosaic of the entire project with specific tasks and in alignment with the other\nPhenoMix\ndoctoral students and postdocs for which recruiting is also going on currently. Overall tasks of the project include:\n•\nPlanning, conducting and evaluating field and post-harvest laboratory experiments\n•\nPerforming statistical analyses, including AI-based approaches\n•\nPresentation of results at national and international events and publication in peer-reviewed and in practice-oriented journals\n•\nOrganisation of national workshops for growers, food industry and consumers\n•\nAssistance in plot establishment, maintenance, monitoring, and harvest across all Work Packages of\nPhenoMi\nx.\nThis full-time position is funded for four years. Salary and social benefits are provided according to ETH Zurich rules. The place of work will be at Agroscope in 8046 Zurich-Affoltern.\nProfile\n•\nA MSc degree in agricultural sciences, biology, ecology or in a related field.\n•\nStrong interest in applied interdisciplinary research and enjoyment of complex field experiments\n•\nParcours professionnel in planning laboratory and field experiments as well as in statistical analyses (e.g. R)\n•\nPerformance-\noriented, team player and open-minded personality\n•\nExcellent standard of written and spoken English\n•\nGood writing skills\n•\nDriver’s license\n•\nBackground in niche crops and good oral communication skills in German are beneficial\nWorkplace\nWe offer\n•\nYour job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society\n•\nYou can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits\nWorking, teaching and re",
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    "title": "PhD Position: Molecular Thermodynamics and Transport Modeling for the Energy Transition",
    "description": "Poste a pourvoir : PhD Position: Molecular Thermodynamics and Transport Modeling for the Energy Transition -- Zurich -- myScience.\n\nETH Zurich propose une thèse en thermodynamique moléculaire.\nTâches\n•\nDévelopper des modèles pour décrire le transport dans les membranes.\n•\nQuantifier les performances des nouveaux matériaux membranaires.\n•\nEncadrer des projets d'étudiants et publier des résultats.\nCompétences\n•\nMaster en ingénierie chimique ou domaine connexe requis.\n•\nExpérience en Python et développement de logiciels scientifiques.\n•\nCapacité à travailler de manière autonome et à communiquer.\nPhD Position: Molecular Thermodynamics and Transport Modeling for the Energy Transition\nEidgenossische Technische Hochschule Zürich, ETHZ\nWorkplace\nZurich\n- Zurich region - Switzerland\nCategory\nEnvironment | Chemistry\nPosition\nJunior Researcher / PhD Position\nPublished\n29 May 2026\nClosing Date\n8 June 2026\nPhD Position: Molecular Thermodynamics and Transport Modeling for the Energy Transition\n100%, Zurich, fixed-term\nThe Molecular Engineering Thermodynamics (MET) group at ETH Zurich is looking for a doctoral student to develop and improve computational tools for the molecular scale description of mass transport in membranes with an application to separation processes. The MET group at ETH Zurich, led by Philipp Rehner, is dedicated to linking rigorous physical molecular models to the design of sustainable processes in chemical engineering. To bridge the scale from molecules to processes, we apply state-of-the art mathematical concepts and tools combined with highly efficient computational methods. A particular focus is on the modeling of interfacial phenomena in process design applications. Our technological focus is on emerging technologies for the energy transition.\nProject background\nA sustainable supply of our energy and materials demands must be built on novel processes that feature renewable feedstocks, green energy supply, and improved energy efficiency. An efficient design of novel processes needs to account for the interactions of molecules and materials with the process performance that occur at interfaces: e.g., adsorbent materials, heat exchanger surfaces, or membranes.\nThe ProMote project establishes an integrated material and process design workflow that - for the first time - incorporates rigorous molecular models for interfacial phenomena directly into the evaluation and design of processes. To bridge the gap between the continuum world of process design and the stochastic nature of molecules, the ProMote project proposes the application of classical density functional theory - a molecular-scale continuum description of inhomogeneous systems - in process design and, therefore, to fuse the scales from molecules to processes.\nTo overcome the computational challenge of applying molecular models at process scales, the project combines efficient mathematical concepts like automatic differentiation with backpropagation - the same concept that powers machine learning and artificial intelligence everywhere - with rigorous physical models that are robust and interpretable due to their physical constraints. In the ProMote project, the integrated design workflow will be demonstrated for three emerging technologies: carbon capture, high-temperature heat pumps, and membrane separations.\nJob description\n•\nYour primary task will be to develop and implement models for the molecular description of transport resistivities in micro- or nanoporous materials\n•\nThe models will then be used to quantify mass transport through membranes in order to evaluate the performance of novel membrane materials in industrial separation processes\n•\nYour role will also involve mentoring and co-supervising student projects and theses\n•\nYou will engage in various group and institute duties and activities\n•\nAs an integral part of your work, you will publish your results in peer-reviewed journals and present them at international conferences\nProfile\n•\nYou meet the requirements for a doctoral program at ETH Zurich and have an excellent Master’s or diploma in chemical engineering, process engineering, mechanical engineering, physics, energy science & technology, physical chemistry, or a related field\n•\nIdeally, you already have experience working computationally and developing scientific software\n•\nExperience in Python is highly recommended, additional knowledge of performance-\noriented modeling frameworks, either based on Python (e.g., JAX, Pytorch) or other programming languages (e.g., C++, Rust, Julia) are welcome\n•\nYou are interested and able to develop thermodynamic models while gaining a solid understanding of the underlying physical processes\n•\nThe ability to work independently and excellent communication and writing skills in English complete your profile\nWorkplace\nWe offer\nWe offer a full-time position for the duration of your doctoral studies, starting upon agreement with the earliest s",
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    "title": "Postdoctoral researcher in optimization for robust railway timetables",
    "description": "myScience ouvre un poste de Postdoctoral researcher in optimization for robust railway timetables a Zurich.\n\nPostdoctorant en optimisation des horaires ferroviaires à l'ETHZ. Rejoignez une équipe engage à Zurich pour améliorer la performance des transports.\nTâches\n•\nDévelopper des modèles d'horaires robustes pour minimiser les retards.\n•\nAnalyser les impacts de différents scénarios de retards sur le réseau.\n•\nCollaborer avec l'industrie pour intégrer des solutions pratiques.\nCompétences\n•\nDoctorat en sciences du transport, mathématiques ou domaines connexes.\n•\nCompétences en programmation et optimisation mathématique requises.\n•\nExcellentes capacités de communication et travail en équipe.\nPostdoctoral researcher in optimization for robust railway timetables\nEidgenossische Technische Hochschule Zürich, ETHZ\nWorkplace\nZurich\n- Zurich region - Switzerland\nCategory\nEnvironment | Computer Science\nPosition\nSenior Scientist / Postdoc\nPublished\n19 May 2026\nClosing Date\n6 July 2026\nPostdoctoral researcher in optimization for robust railway timetables\n100%, Zurich, fixed-term\nDespite the excellent quality of public transport systems in Switzerland, the railway system needs to increase its performance (quality, for instance, travel time, and delays) and capacity (amount of services run) and attract more travellers to match the ambitious targets from policy and environmental goals. One key aspect of traditional railway transport systems is their plan, which is based on predetermined routes, lines, and scheduled times, with little possibility of adjusting to unplanned and unexpected circumstances. On the other hand, delays and disruption might affect many services throughout a network by means of propagation. The project focuses on timetable planning that is able to minimize delays and their impacts.\nTo do so, large-scale optimisation addresses the railway timetabling problem. Typically Mixed Integer Linear Programming approaches are used, which are mathematically complex, and with some limits, when modelling real-life complexity. Incorporating robustness against delays is an additional important aspect. This project assumes that we are able to quantify how small delays develop and propagate throughout the network; how larger disruptions develop and propagate in the network. Given this, we want to determine robust timetables, with suitable choice of buffers and running time reserves. Those timetables, under delays, are able to perform quantitatively better (i.e. less delays, fewer larger delays,...).\nThis position will be available, with an ideal starting date between September 2026 and April 2027, or further upon agreement; the planned duration of the initial contract is one year, to be extended based on successful performance, for up to 2 years.\nProject background\nThe focus of this project is to understand how delays occur and propagate in a real-life railway network. This exposes some complex dynamics as response to external events (small delays, larger disruptions), and some impact, which can be characterized by simulation models. The scientific challenge involves designing timetabling models that can deal with the complexity of existing system dynamics, in a variety of integrative aspects.\nThe project is designed in collaboration with industry player operating as railway infrastructure manager. The project bases on available solvers for non-periodic timetabling, which include MILP and Logic-Based Benders-Decomposition approaches. This research is carried out within an international cooperation with the Complex Systems group at Utrecht University, in the Netherlands.\nJob description\n•\nexpand and consolidate existing timetabling models to include constraints from limited resources; and complex dynamics resulting from variable choices.\n•\nexpand scope of scheduling models to tackle multi objective problems, and non-scalar objective functions (like probability of delays).\n•\nstudy local and systemic impacts of timetables when exposed to expected or speculative delay dynamics.\nProfile\nIdeally, you have (or are about to receive) a Doctoral Degree in transport sciences, management/ decision sciences, applied mathematics, econometrics, statistics, computer science, physics or related fields.\nYour research track is consistent and shows a track record, or clear potential, for analysing, modelling, control, and optimisation of transport systems. You are highly motivated and self-driven, with a clear research vision, academic ambition, and excellent communication and writing skills (fluent spoken and written English is mandatory). Moreover, the following skills are expected of a promising candidate:\n•\nComputer science and ability to program independently complex software\n•\nAbility to model and work with algorithmic design, existing software and data provided by industrial partners\n•\nKnowledge of mathematical optimisation (MILP, IP, LP) and/or control sciences\n•\nTeam working and communi",
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    "title": "Postdoctoral Position in Machine Learning for Automated Plant Phenotyping (PhenoMix Project)",
    "description": "Vous cherchez un emploi de Postdoctoral Position in Machine Learning for Automated Plant Phenotyping (PhenoMix Project) a Zurich ? myScience recrute.\n\nETH Zurich cherche un postdoctorant en Machine Learning pour le projet PhenoMix. Une occasion unique d'innover dans la phénotypage automatisé.\nTâches\n•\nDévelopper des modèles de machine learning pour l'estimation des traits des plantes.\n•\nCollaborer avec des experts en sciences agricoles et validation sur le terrain.\n•\nProduire des ensembles de données multimodales pour améliorer les méthodes de phénotypage.\nCompétences\n•\nDoctorat en informatique, machine learning ou sciences connexes exigé.\n•\nExpertise en machine learning et vision par ordinateur requise.\n•\nCompétences en programmation Python et gestion de données complexes.\nPostdoctoral Position in Machine Learning for Automated Plant Phenotyping (PhenoMix Project)\nEidgenossische Technische Hochschule Zürich, ETHZ\nWorkplace\nZurich\n- Zurich region - Switzerland\nCategory\nComputer Science | Environment\nPosition\nSenior Scientist / Postdoc\nPublished\n6 May 2026\nPostdoctoral Position in Machine Learning for Automated Plant Phenotyping (PhenoMix Project)\n100%, Zurich, fixed-term\nThe Swiss Data Science Center (SDSC) is a national research infrastructure in data science and artificial intelligence (AI) of the ETH domain, with EPFL and ETH Zurich as founding partners. Its mission is to support academic labs, hospitals, industry and public sector stakeholders, including cantonal and federal administrations, through their entire data science journey, from the collection and management of data to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen), the SDSC provides expertise and services to various domains, such as health and biomedical sciences, energy and sustainability, climate and environment, and large-scale scientific infrastructures.\nThe Swiss Data Science Center (SDSC) and the ETH Zurich’s Crop Science Group are seeking a Postdoctoral Researcher for the PhenoMix project, a Swiss National Science Foundation (SNSF) funded initiative.\nThis role sits at the intersection of machine learning, computer vision, agricultural sciences, and plant phenotyping. The position focuses on Automated Trait Estimation using Machine Learning, developing novel data science methods for crop mixture phenotyping.\nThe position will be based at the SDSC Zurich office (Andreasturm), with close collaboration with the Crop Science Group (Prof. Walter), the Grassland Sciences Group (Prof. Buchmann) at ETH Zurich’s Department of Environmental Systems Science (D-USYS), and with AGROSCOPE (Dr. Vogelgsang).\nProject background\nContext:\nThe PhenoMix project addresses the critical challenge of automated phenotyping for crop mixtures -- a promising agricultural practice with significant potential for sustainable food production. The project leverages the Field Imaging Platform (FIP), a state-of-the-art high-throughput phenotyping facility, along with field experiments to generate unprecedented multi-modal datasets of pure stands and crop mixtures. The project will also contribute to the creation of new generation phenotyping datasets - including 3D reconstructions and derived trait information - and related models, which will be made publicly available\nThe postdoctoral researcher will create novel data science tools and automate processing of image time series, plant trait information, and 3D reconstructions. The work will bridge advanced machine learning methods with practical agricultural applications, developing models that can transfer knowledge across different imaging platforms and environmental conditions. The postdoc will be responsible for delivering advances and solutions that not only advance the state-of-the-art, but also have real-world impact for farmers, breeders, and researchers in the field of plant phenotyping.\nCollaboration:\nThe postdoctoral researcher will be part of a highly collaborative and interdisciplinary project, working closely with experts in machine learning, plant phenotyping, crop sciences, and field validation. The project is designed to foster knowledge exchange and collaboration across disciplines, ensuring that the developed methods are both scientifically rigorous and practically relevant.\nThis project brings together expertise from multiple leading groups. The SDSC provides expertise in machine learning, computer vision, and data science infrastructure, serving as the primary host institution for this position. The Crop Science Group (Prof. Achim Walter, ETH Zurich) operates the Field Imaging Platform (FIP) and and brings deep expertise in high-throughput plant phenotyping and crop science, providing access to cutting-edge infrastructure and datasets. The Grassland Sciences Group (Prof. Nina Buchmann, ETH Zurich) contributes key expertise in plant ecophysiology, biodiversity and plant ec",
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