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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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of Alabama and beyond. The successful candidate will apply tools including (but not limited to) Data Acquisitions, Data Mining, Data Visualization, Machine Learning, Statistics, Optimization and Simulation in
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of optimizing pipelines for large-scale genomic projects. Special Instructions Required documents: CV Research summary of PhD work. Cover letter describing your interest in the lab and initial ideas for new
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analyses. Design, maintain, and optimize computational pipelines and software tools for integration of multi‑omics and clinical datasets to uncover mechanisms of tumor evolution and therapeutic resistance
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do: Design, fabricate, characterize, and optimize electrochemical biosensing technologies for real-time detection. Develop and implement novel surface chemistries to improve sensor performance
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reliability. The research will be conducted within the STRENGTHENS (Studies to Refine and Enhance Next Generation Therapies to Prevent Suicide) Group. STRENGTHENS focuses on developing, testing, and optimizing
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 4 hours ago
to develop and apply data-mining tools Reviewing, extracting, and harmonizing data from literature Constructing and enhancing training databases for modeling purposes Learning to develop, validate and optimize
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of medicinal chemistry. The candidate will be responsible for designing, synthesizing, and optimizing molecules targeting GPCRs (cannabinoid receptors; allosteric and orthosteric) and ion channels (a4b2 nAChR
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innovative microfluidic technologies. Responsibilities: Designing and conducting experiments to study microbial communities using microfluidic platforms. Developing and optimizing microfluidic devices for high
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Models , Large Scale Optimization , Machine Learning , Natural Sciences , Public Interest Tech Computational Biology / Data Analytics , Computational Biology , Computational, Quantitative or Systems