17 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"FEUP" Fellowship positions at University of Michigan in United States
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highly qualified, self-motivated post- doctoral fellow to join our research program in computer-aided diagnosis and AI (CAD-AI). Responsibilities* The research will involve development of decision support
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experimental team to build and apply analytical frameworks that translate these data into mechanistic insight and therapeutic hypotheses. As part of the Bioinnovations in Brain Cancer initiative, the Fellow will
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of consciousness, including sleep, anesthesia, coma, and non-ordinary states induced by psychoactive compounds. Responsibilities include experimentation and data collection in human participants using
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Apply Now How to Apply Upload a resume/CV, cover letter, and contact information for two referees (combined into a single PDF) via the U-M applicant system. Questions about the position should be
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contact information for at least two referees who can supply letters of recommendation upon request. Inquiries and additional materials can be sent to lzahodne@umich.edu. Job Summary The Department
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, operation of the scanner, data acquisition and analysis, image evaluation, and statistical analysis. The fellow will also be expected to prepare manuscripts and conference abstracts related to projects and
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, and research. The 884-bed medical center currently employs 2,700 faculty, cares for ~48,000 inpatients per year and provides approximately 2.3 million clinic visits and 54,000 surgeries per year. Data
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research projects in computer vision, machine learning, AI, and robotics. Projects may include physically-grounded AI guidance agents, modeling of multimodal data, and generative AI systems for situated
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, and in vivo mouse models, working in close partnership with the lab's computational team to generate data-rich spatial multi-omics datasets that drive discovery. As part of the Bioinnovations in Brain
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. Must have experience with analysis of sequencing data (RNA-seq, CUT&RUN, etc) and/or sufficient computation background to learn these analyses. Must have a strong publication history supporting potential