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Field
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to therapeutic discovery You bring PhD in computational biology, bioinformatics, computer science, or related field Strong coding skills (Python required; ML frameworks preferred) First-author publication(s
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biology, or a related field Experience designing, executing, analyzing, and interpreting quantitative experiments, including high-throughput screens. Experience with coding software such as Python, R, and
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Organization U.S. Food and Drug Administration (FDA) Reference Code FDA-CBER-2026-0059 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete
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competitors/frameworks (Mojo and JAX) for extreme‑scale heterogeneous systems. The selected researcher will explore how autonomous AI agents and LLM‑driven code generation can co‑evolve with next‑generation
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multi-scale modeling across spatial and temporal domains, including residual stress and distortion in large-format structures Experience with CAD/CAM, MATLAB, G-Code Knowledge and/or experience with solid
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engine modeling code. Perform high-fidelity CFD simulations of turbulent and reacting flows pertaining to gas turbines and detonation engines using spectral element method (SEM). Perform scalability
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by working on research projects in AI safety and robotics, contributing across the full research lifecycle: algorithm and system design, code development, experimental validation, and scientific
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grant writing or contributing to funded projects. Strong coding experience using R and Python for data analysis. Expertise in the biological interpretation of multi-omics datasets (RNA-seq, proteomics
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international datasets (specifically Sub-Saharan Africa). Prior experience with clinical or healthcare data (EHR, registries). High proficiency in coding with R or Python for data cleaning, analysis, and
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and Environmental Engineering at the University of New Hampshire. The successful candidate will be responsible for developing and coding workflow processes and designing experiments for multisensory data