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of protein variants Demonstrated experience with pooled, massively parallel screening approaches coupled to next-generation sequencing Skills to independently establish assays in yeast as a host system You
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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scaled up to handle large numbers of samples in massively parallel, low-cost analysis systems. Before such systems can be realized, the electromagnetic response of biochemical samples must be understood in
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. Programming & Software Development: Proficiency in Python, PyTorch, JAX, or other ML frameworks Computing: Some experience with large-scale datasets, parallel computing, and GPUs/TPUs. Algorithm Development
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of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
job scheduling, resource allocation, and parallel computing. Special Physical/Mental Requirements N/A Campus Security Authority Responsibilities Not Applicable. Special Instructions Quick Link https
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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. The appointment is for one year with a
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molecular motors and RNA-folding. In a parallel effort, we significantly enhanced the biophysical capabilities of an atomic force microscope (AFM). Specifically, we achieved sub-pN force precision and
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research teams. Preferred Qualifications Experience with commercial and/or open-source GIS tools and technologies. Experience in parallel computing (e.g., MPI, Spark) and/or cloud computing (e.g., AWS
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, chunking, parallelization; Dask/Spark a plus). Experience using or building agentic/LLM-enabled workflows for data discovery, extraction, and normalization, with attention to provenance, reproducibility, and