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ICT Services & Applications. Your role This position sits at the interface of machine learning, uncertainty quantification and computational biomechanics. You will work within the Legato group and in
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with contemporary machine learning methods. We are looking for an ambitious Postdoc who will lead our efforts on the design, implementation, and training of mechanistic models of cell organization. In particular, we
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) Experience in genomics, single-cell data, or machine learning (preferred) Why this is exceptional Build next-generation AI models of the human genome Work with one of the richest longitudinal PD datasets
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change constraints to reduce the environmental impact of agriculture. Ideal candidates have experience in using biogeochemical models at the field and regional levels, as well as exploring machine learning
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the analysis of complex biomedical data using state-of-the-art AI and agentic system approaches, as well as the development of novel machine learning and deep learning algorithms. Your work will range from
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modelling methods to design resistance-proof antibiotics. You will join an interdisciplinary team, integrating machine learning, medicinal chemistry and microbiology. You will work with Asst. Prof. Eli N
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programming and instrument control using Matlab, Python, Labview etc Machine / deep learning expertise Strong analytical skills and ability to work in a multidisciplinary team Excellent communication and
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025 BRIDGES project GenePPS, which investigates how machine learning can enable
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analyses. Machine learning for biological data (e.g., protein language models, transformers, generative models) and interest in building interpretable tools for experimental colleagues. Qualifications PhD