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coverage effective on your very first day 2:1 Match on retirement savings Responsibilities* Working alongside with wet-bench scientists and PhD candidate (both with and without computational experience
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, consent 30% - MRI Data Collection and Data Analysis 15% - MR Image Evaluation and Annotation 15%-Conference Abstract and Manuscript Preparation Required Qualifications* Applicants should have a PhD
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Apply Now Required Qualifications* A PhD is required for this position. Modes of Work Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department
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fashion, analyze data, develop new research methodologies, prepare research papers, and contribute to grant applications. While funding is currently available for the position, the candidate will be
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analyses for latent spaces formed from neural, genetic, and behavioral data. Mission Statement Michigan Medicine improves the health of patients, populations and communities through excellence in education
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experiences to help further our mission. The successful candidate(s) will have: Completed a doctoral degree program (MD, PhD, DrPH, EdD, or equivalent) by the starting date. Demonstrated commitment and interest
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multi-omics data integration (e.g.: ATACseq, RNAseq, single cell RNAseq and spatial-omics platforms like CODEX/mIF or 10x Visium). The fellow will work with several research collaborators in the EECS
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all aspects of fieldwork for the 20-year follow-up of the NSAL, including refinement of data collection procedures (e.g. recruitment messaging, survey questionnaire, informed consent documents), re
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data
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, productive team involved in analyzing -omic data from our ongoing clinical trial studies and larger datasets from systemic sclerosis and other fibrotic diseases. Complementing the analytical work by wet lab