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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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. Responsibilities may include: Designing and conducting studies on the clinical impact of GLP-1 and other metabolic therapies Developing and applying computer vision and machine learning techniques to analyze
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of the selected candidate, budget availability, and internal equity. The Fellow will teach one course per year in the Department of Religious Studies at Stanford, give one talk on their research during the term
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electrophysiology. We are seeking a postdoctoral researcher to lead the neuroimaging component of a longitudinal, pediatric drug trial in Neurofibromatosis type 1 (NF1). In this role, you will acquire and analyze
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due
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of urothelial exfoliation in cancer therapeutics. The labs are committed to fostering a highly collaborative and scientifically rigorous environment. This position offers an excellent opportunity to learn about
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offering varied learning opportunities. Required Qualifications: The candidate must have a Ph.D. or M.D./Ph.D. with a focus on cancer biology, cell/molecular biology, or biochemistry. Experience in animal
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and early-onset cases without a known genetic cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been
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, EBV, HBV, HPV) and chemical biology trainees with a willingness and aptitude for learning new experimental systems. Our projects require an adaptable mix of molecular virology as well as protein
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one or more of the following areas is a BIG PLUS: data science (machine learning and AI), cancer biology, animal physiology, organic chemistry, E3-ubiquitin biology, and gene editing. In all cases