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HPC concepts, including parallel computing, distributed systems, and optimization. Analytical skills, problem-solving abilities, and a growth mindset. Additional Qualifications Applicants should be
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Monday, June 1, 2026 : CV. A research statement of no more than 2 pages describing relevant experience in foundation models and AI systems, large-scale or distributed computing, and scientific
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-generation sequencing ( NGS ) data analysis, workflow automation, and cloud computing. This role will support research and production environments where reproducibility, scalability, and performance are
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in Linux/Unix-based high-performance computing ( HPC ) environments and job schedulers (e.g., SLURM or qsub); experience with cloud computing platforms (e.g., AWS , GCP , Terra) is a plus
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modeling brain circuits and neural activity from large-scale, multi-regional recordings Experience with large-scale datasets, distributed training, or high-performance computing environments Expertise in
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cellular biology, including AlphaFold, RFDiffusion, CellCap, or related systems Experience with large-scale datasets, distributed training, or high-performance computing environments Expertise in
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computing environments Interest in scientific applications of AI/ML, including the life sciences Interest in alternative architectures and systems-level approaches to AI Special Instructions Please
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, RFDiffusion, CellCap, or related systems. Experience with large-scale datasets, distributed training, or high-performance computing environments. Expertise in scientific applications of AI/ML in protein
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modeling brain circuits and neural activity from large-scale, multi-regional recordings. Experience with large-scale datasets, distributed training, or high-performance computing environments. Experience
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) and the Martinos Center for Biomedical Imaging (Harvard/ MIT /Mass General). In parallel, there will be opportunities to analyze and publish existing data upon identifying areas of mutual interest