25 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:"-"Dr" Fellowship positions at University of Michigan
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determined in consultation with the department and aligned with the fellows expertise and interests. Required Qualifications* Ph.D. in Linguistics, Computer Science, Cognitive Science, or a related field by
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for one year, with the possibility of renewal based on performance and funding availability. This position reports to Dr. Yara Almubarak. Responsibilities* Work under Assistant Professor on externally
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Qualifications* PhD in computational biology, bioinformatics, data science, or a related quantitative field. Proficiency in Python and/or R; experience with high-performance computing environments. Experience with
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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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for external funding. Assist with supervision and training of junior lab personnel Required Qualifications* PhD or equivalent in the biomedical sciences. Must be able to perform basic molecular and cellular
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experience that directly relate to the duties described below. Additional materials can be sent to agearhar@umich.edu. Job Summary The FAST Lab (Food and Addiction Science & Treatment Lab) at the University
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have the chance to perform experiments while supervising or collaborating with students. Who We Are Michigan Engineering provides scientific and technological leadership to the people of the world. We
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methods to generate conclusions based on data. 4. Assist in preparing and writing technical reports, peer-reviewed conference and journal publications; and, present results at local and national engineering
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, or related field Strong research background in computer vision, machine learning, artificial intelligence, and/or robotics Established record of publication in the top venues in the field (e.g. CVPR
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functional MRI (fMRI), electroencephalography (EEG), and neuromodulation with low-intensity focused ultrasound (LIFU); computational analysis of fMRI and EEG data; development of new research methodologies