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for antibody repertoire sequencing and AI-driven research initiatives. Lead the integration of NGS into discovery workflows (in-vivo and in-vitro), emphasizing data generation for machine learning applications
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(thedonnellycentre.utoronto.ca ). Required Qualifications: We are looking for postdocs that have excellent molecular biology skills and/or a strong computational background including machine learning approaches. Candidates should
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statements Up to three scientific contributions (not required) Three letters of reference Application materials, including the letters of reference, are due February 3, 2026 at 3:00 pm ET. Learn more and apply
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-Universität zu Berlin Some prior experience in experimental laboratory work and instrumental analytics, along with careful and safety-conscious working practices Ability to perform computer-based evaluation
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immunology Experience with T cell engineering (CAR-T, TCR-T) and/or immunopeptidomics is preferred (but not required). At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and
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VwGr. B1 lit. b (postdoc) Limited until: permanent Reference no.: 4984 Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around
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science, or related fields. Proven expertise in machine learning, LLMs, or deep learning architectures and their application to biological or biomedical data. Experience in managing computational resources and
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to learn. Interest in tumor metabolism and a strong desire to gain experience in bulk and spatial metabolomics. Solid bioinformatics skills, including familiarity with tools for analyzing omics datasets and
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individuals. iPSC “Village” systems and CRISPR perturbation to experimentally dissect and validate gene function in controlled, scalable cellular models. Advanced computational genomics, machine learning, and
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Science at MBZUAI focuses on the rigorous statistical and probabilistic foundations of machine learning and data science. We emphasize computational methods for large-scale data and scalable inference