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analytical lab equipment. Collect and interpret all data for all synthesized compounds and intermediates: Any form/type of NMR; Mass spectrometry; HLPC-UV purity. Computational work with Schrodinger molecular
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they are developing Required Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience
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a postdoctoral fellow to provide primary analysis of imaging and other data related to the Udall Center's primary research study and a similar study, the University of Groningen Dutch Parkinson Cohort
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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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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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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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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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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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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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, 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