832 professor-computer-"https:"-"https:"-"https:"-"https:"-"Keele-University" Postdoctoral positions in United States
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to employment start date. Additional Required Qualifications Relevant Ph.D. or Ph.D. candidate in Electrical Engineering or Computer Science or related fields. Solid background in power systems dynamics and
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to independently design, execute, and troubleshoot experiments Strong computational skills for processing complex cryo-EM datasets Enthusiasm and demonstrated ability to rapidly learn new techniques Prior training
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may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research
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post-doctoral research associate to simulate amorphous materials and crystallization reactions using atomic-scale simulations. As a post-doc, you will utilize high performance computing and rare event
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samples and characterize dynamic behaviors. The candidate will be part of a highly collaborative team and actively interact with other groups, including optics, computation, and time-resolved research
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biological, chemical, and catalytic research . The center has strong thrusts in polymer design and upcycling, separations, synthetic biology and bioconversion, analytical sciences, computational modeling, and
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of wet-lab and computational methods including but not limited to next-generation sequencing and data analysis, spatial transcriptomic sequencing and analysis, single-cell studies, advanced cell
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. Bradley Maron, Professor of Medicine, at bmaron@som.umaryland.edu. Qualifications Applicants are required to have a Ph.D. or M.D. and expertise in lab techniques. Familiarity with experimental techniques
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. Technical Proficiency: Skilled in laboratory or clinical research techniques depending on the research focus. Data Analysis: Proficiency with statistical and computational tools for quantitative and
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy