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Field
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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/deep learning with GWAS/sequencing data and other types of omic data, as in Mendelian randomization and TWAS. In addition to new methods development and evaluations, the job responsibilities include
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computational approaches to biological systems. Its core activity is the development of deep learning methods for protein design and optimization, with applications in biology and medicine. - activities: We
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) The postdoc will contribute to lab duties, which is evenly distributed among all lab members. Lab: https://www.helabucb.org/ Qualifications Basic qualifications (required at time of application) PhD
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following table(s) for the current salary scale(s) for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-oct-2025-scales/t23.pdf . The current minimum salary range
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qualifications PhD in Microbiology, Computational Biology, Genomics, Systems Biology, Statistics, Machine Learning or related discipline Publication record in Microbiology, Metagenomics, Metabolic/Statistical
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sponsorship. *Duties/responsibilities: -performing high level experimental, theoretical, and numerical research and data analysis (55%) -presentation publication, and proposal preparation (20%) -mentoring PhD
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sponsorship. *Duties/responsibilities -performing high level experimental, theoretical, and numerical research and data analysis (55%) -presentation publication, and proposal preparation (20%) -mentoring PhD
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, Artificial Intelligence, Computer Science, or an equivalent qualification. You have in-depth knowledge of deep learning techniques. You have experience with Python. You have in-depth knowledge of knowledge
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Requirements Research FieldComputer science » Computer systemsEducation LevelPhD or equivalent Skills/Qualifications Knowledge • Solid understanding of machine learning, deep learning, and modern AI techniques