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with biological datasets; experience with R, Python, or omics analysis pipelines is advantageous but a keen willingness to learn is equally valued Language Requirements: Applicants must demonstrate
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- Knowledge in programming in Python or R - Familiarity with machine learning or deep learning methods is a plus - Interest in plant genomics, evolutionary biology, or comparative genomics - Proficient in
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, BWA, STAR, GATK, VarScan, DESeq) Proficiency in Linux and programming languages such as Python, R, MATLAB, or Perl Excellent written and verbal communication skills in English, along with a
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systems, automated workflows, or LLM-based development environments (e.g., OpenAI Codex, Claude Code, or similar) is a plus Proficiency in Python, Linux, and HPC environments Experience working with
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skills in Python and/or R (Java/Perl an advantage). Familiarity with Linux/UNIX systems and shell scripting. Excellent understanding of NGS data processing, alignment, variant calling, annotation, and
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, biomedical informatics, or a related quantitative field; outstanding candidates at either level are encouraged to apply Strong programming skills, especially in Python; experience with TypeScript/JavaScript
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strong background in machine learning and/or computer vision is required, along with solid programming skills in Python and experience with deep learning frameworks (e.g. PyTorch). Prior research
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dedicated learning opportunities. What you'll bring Essential A Ph.D. in Computer Science, Physics, Engineering, Biology, or related fields. Experience with machine learning. Experience with scientific python
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rigorous documentation and version control. Solid programming and data-analysis skills (e.g., Python) and experience working with structural biology and protein-design software/toolchains (e.g., Rosetta
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Assist with deployment and support of AI software stacks, containerized research environments, and Python-based computational workflows. Help optimize GPU utilization, data throughput, storage access