14 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" research jobs at University of Basel
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between behavioral and computer scientists. The ideal candidate has some knowledge in both areas, and the specific behavioral domain is open to discussion. Project B – Understanding and Countering
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performance across development. Possible research topics within this position include, among others, “Embodied Learning", physical activity and sport in Developmental Disorders, and the cognitive effects
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computational analyses of single-cell, spatial transcriptomics, and multi-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI
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immediately and will remain open until filled by suitable candidate. Where to apply Website https://academicpositions.com/ad/university-of-basel/2026/postdoctoral-fellow-c… Requirements Research FieldBiological
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between behavioral and computer scientists. The ideal candidate has some knowledge in both areas, and the specific behavioral domain is open to discussion. Project B – Understanding and Countering
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competencies. Optional: A letter of support from your current institution. Please apply online by 15 January 2026: https://biped.biozentrum.unibas.ch/apply/fellowship-for-clinicians Review of applications will
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) Experience in deep learning algorithms is a plus Ability to work in a highly international team and interdisciplinary project applicants are expected to have excellent language skills in English Opportunity
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mates; help with administrative tasks, conference organization, communication tasks. You will be encouraged to: take on a co-mentoring role for the project's two doctoral students; teach one or two
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the lab, and at the same time to play an active role in shaping and creating an inspiring research and working environment. In line with our and Uni Basel values (https://www.unibas.ch/en/Research/Values
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-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI approaches to biological questions Collaborating closely with