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. Collaborate with world leaders in neuroscience, including partners at Harvard/MGH, INSERM–Paris Saclay, and Mayo Clinic. Contribute to research with direct translational relevance for TBI, Alzheimer’s
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the Parallel Systems Lab ( https://psl-ntu.github.io ) at NTU’s CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI workflows
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statistical mechanical theory to analyze the simulation results Basic understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred
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develop both high-throughput and gene-specific approaches for determining the functional consequences of human genetic variation. Current and developing projects include massively parallel splicing
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, and reproducible code development skills; distributed or parallel computing is a plus. Experience designing and executing field experiments in urban or environmental settings, with willingness to
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Albert Einstein College of Medicine (Bronx, NY) | New York City, New York | United States | 2 days ago
stem cells. 2) Functional genomics of noncoding regulatory variation Projects will use massively parallel reporter assays, CRISPR-based screens, and genome editing to test noncoding variants, map
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environments, and high-performance or parallel computing is desirable. The candidate will also prepare technical documentation, reports, peer-reviewed publications, and presentations and collaborate
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team integrates innovative high-throughput sequencing technologies, bioinformatics approaches, and multi-scale models to elucidate RNA-mediated endothelial biology in the context of diabetes. In parallel
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cellular endpoints. In parallel, the fellow will perform complementary functional studies to investigate tumor cell state, lineage programs, and therapeutic response. This work will incorporate a broad
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density functional theory. Refereed publications in these areas commensurate with career stage. Experience of FORTRAN and python programming. Previous experience in developing and using parallel