40 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral positions at University of Maryland, Baltimore
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areas: · Metagenomic and metatranscriptomic sequencing analysis · Single-cell RNA-seq and proteomic/metabolomic data integration · Integration of clinical and multi-omic microbiome data
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positions: Qualifications 1. Computational Biology & Data Integration Using multi-omics microbiome analysis, single-cell transcriptomics, and machine learning–based biomarker prediction models, this project
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to Thomas Ernst, Ph.D. (ternst@som.umaryland.edu ) with a cover letter highlighting key qualifications and experience, current CV and contact information for three referees. Qualifications The position
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imbalanced cross-sectional imaging data are especially well-suited for the position . The postdoctoral researchers will develop algorithms for deployment at our prestigious R Adams Cowley Shock Trauma Center
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for preclinical imaging with opportunity to gain a variety of translational research skills, including advanced image processing, data analysis, and novel imaging techniques, such as MRguided Focus Ultrasound
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research and experience in endothelial cell biology is a plus. If interested please email a CV, a short statement of research interests, and the names and contact information for three references to: Dr
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the central nervous system to maintain whole-body thermogenesis, energy balance, and metabolic health. Additional information on our research projects can be found in our publications, including Cell Metabolism
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to work independently is essential. Salary commensurate with experience. To apply for this position or to seek additional information, please contact Dr Marcela Pasetti by e-mail: mpasetti@som.umaryland.edu
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scientific research involving human cell lines, mouse models, and clinical samples. Interested candidates should email CV and contact information for three references to Valeria R. Mas, MS, PhD, FAST Professor
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software for imaging processing of structural and functional MRI data (e.g., SPM, FSL, Freesurfer, MRIStudio) is highly desirable. To apply, please send a letter of interest and CV to linda.chang@umm.edu