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Field
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focus will be on introducing new AI models to chart the chemical âœdark matterâ of the mammalian metabolome; examples of such models include large supervised or self-supervised AI models for mass
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-associated systemic metabolic dysfunction. We use genetically engineered mouse models, patient-derived organoid cultures, optical redox sensors, chemical proteomics, single-cell sequencing, metabolomics, and
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platforms supporting metabolomics, systems biology, and molecular physiology Strong interdisciplinary partnerships across engineering, veterinary medicine, agriculture, and biomedical sciences A vibrant and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
industry-relevant experience through collaborations with the Center for Integrative Chemical Biology and Drug Discovery (UNC) and the Metabolomics and Exposome Laboratory (UNC). These collaborations will
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(https://endomic.github.io) aims to develop artificial intelligence and statistical-learning methods capable of identifying robust and clinically meaningful disease endotypes from heterogeneous, multimodal
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Associate II will work at the interface of basic and translational science, combining genetic, pharmacological and molecular biology/biochemistry approaches with the latest metabolomics, metabolic flux
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=28177 PhD position (m/w/d) Stellenanzeige merken Stellenanzeige teilen starting at the earliest
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Nutrition Postdoc Appointment Term: Fixed term for one (1) year with opportunity for renewal Appointment Start Date: ASAP Group or Departmental Website: https://colmanlab.stanford.edu/(link is external) How
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at the Department of Human Nutrition and Metabolomics permanent contract Where to apply E-mail [email protected] Requirements Research FieldMedical sciences » Health sciencesEducation LevelPhD or equivalent Skills
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project will utilize hematopoietic stem cells from mice to identify metabolic factors that drive stem cell aging using flow cytometry, RNA/DNA sequencing, proteomics, metabolomics, immunofluorescence