17 machine-learning "https:" "https:" "https:" "UCL" research jobs at University of Basel
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approaches Applying statistical modeling, causal inference, and machine learning approaches to identify determinants of developmental robustness Applying causal inference approaches to identify critical
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Hospital, Copenhagen). The successful candidate will be responsible for designing and implementing the predictive modeling strategy of the project. This includes: Developing machine-learning prediction
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
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optical simulation skills (Preferably in Zemax) Strong programming skills (preferably in Python) Experience in deep learning algorithms is a plus Ability to work in a highly international team and
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Postdoc in Biomedical Ethics The Institute for Biomedical Ethics at the University of Basel (IBMB), Switzerland (https://ibmb.unibas.ch/ ), is looking for an enthusiastic collaborator to join our
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Vision, or a related field. Proven experience in photogrammetry, image-based 3D reconstruction, and cultural heritage digitization. Solid programming skills (e.g., Python, C++) and familiarity with
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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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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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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