50 phd-energy-or-power-or-grid-or-optimization Postdoctoral positions at The University of Arizona
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., model-based, optimal, learning-augmented control), perception, and planning modules; run structured experiments and benchmarking. Architect high-quality research codebases in C++/Python/C# (e.g., ROS/ROS
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skills Excellent written and oral communication skills Ability to work independently and in collaborative, multidisciplinary teams Minimum Qualifications Doctorate degree such as PhD or MD in biochemistry
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mechanisms. Cutting-edge research models (eg. primary cell/organoid cultures, mouse models and human clinical samples) and technologies (e.g. scRNA-seq, CRISPR) are utilized in the lab. the PI is highly
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independently as well as in a team under direction of the principal investigator, and have the ability to communicate in a clear, concise manner orally and in writing. This position is eligible for visa
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, demonstrated by a strong publication record: 1) bioinformatics and related areas; 2) cell and molecular biology and related areas; or 3) animal model physiology and related areas. Candidates must have a PhD, or
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record: 1) bioinformatics and related areas; 2) cell and molecular biology and related areas; or 3) animal model physiology and related areas. Candidates must have a PhD, or MD/PhD degree, and be self
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Associates. The ideal candidates will possess a doctoral degree (PhD or MD) and have a strong background in molecular biology and physiology. There are three major projects in the lab: 1) studying the role
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Minimum Qualifications Doctorate degree such as PhD or MD in biochemistry, molecular biology, immunology or related field is required. Preferred Qualifications Experience with in vitro cell models and in
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, etc.). Leveraging computational geometry methods for advanced manufacturing applications. Advancing topology optimization methods for lightweight and high-performance designs. Collaborating with faculty
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from antigen presentation, prediction of immunogenic neoantigens, to T cell-mediated control of cutaneous squamous cell carcinoma and melanoma, utilizing immunological, cellular and molecular biological