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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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biology, bioinformatics, genetics, AI, machine learning, computer science, or a related field. Demonstrated experience analyzing single-cell and/or spatial genomics datasets is a plus but not necessary
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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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. We are seeking highly motivated individuals who are passionate about science, learning and having fun. Candidates with a strong background in molecular and cellular biology, and/or experience in
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are an interdisciplinary research team that integrates single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine learning to investigate how the human brain
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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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, 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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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning
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, permitting, economics, and workforce constraints, differentiating among public (federal, state, local) and private land ownership contexts. Assess biochar technologies (yield, emissions, mobility, CapEx/OpEx