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practical applications, including solving mathematical reasoning problems. The ideal candidate has a strong background in machine learning and an interest in bridging rigorous theoretical insights with
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machine learning approaches Collaborating with experimental and clinical research partners Support and preparation of scientific reports and journal articles
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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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(https://www.unibas.ch/en/Research/Values-Ethics/Diversity-and-Inclusion.html ), we are committed to sustain and promote an inclusive culture, ensure equal opportunities and value diversity and respect in
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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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the project, supported by Dr. Adamo and close collaboration partners, within an environment that encourages academic freedom and scientific independence. In line with our and Uni Basel values (https
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the project, supported by Dr. Adamo and close collaboration partners, within an environment that encourages academic freedom and scientific independence. In line with our and Uni Basel values (https