7 machine-learning-phd Fellowship positions at University of Michigan in United States

  • University of Michigan | Ann Arbor, Michigan | United States | about 6 hours ago

    seekinga Postdoctoral Research Fellow to work on projects related to molecular design including small molecules and proteins using biophysics and machine learning. Responsibilities* The selected candidates

  • University of Michigan | Ann Arbor, Michigan | United States | about 7 hours ago

    to generate and publish high-impact machine learning research. Collection, curation, and maintenance of neural datasets Building lab equipment and software infrastructure for neural engineering experiments

  • University of Michigan | Ann Arbor, Michigan | United States | 2 months ago

    your specific interest in the position and outline skills and experience that directly relate to this position. Summary The Machine Learning in Neurosurgery (MLiNS) Laboratory in the Department

  • University of Michigan | Ann Arbor, Michigan | United States | about 1 month ago

    performance analysis of analytical to experimental data Desired Qualifications* Machine learning expertise to analyze radiology images and histology, to detect ossification, analyze soft and hard tissue micro

  • University of Michigan | Ann Arbor, Michigan | United States | about 2 months ago

    support staff. Required Qualifications* PhD degree or equivalent in epidemiology or a related field Experience with analysis of health data linked to contextual and environmental information Analysis

  • University of Michigan | Ann Arbor, Michigan | United States | 3 months ago

    * ?         Knowledge of control theory, statistical and probabilistic methods, optimization, machine learning, robotics, or related fields. ?         Passion for water, the environment, and open source. ?         Strong

  • University of Michigan | Ann Arbor, Michigan | United States | 3 months ago

    spending accounts for healthcare and dependent care expenses. Learn more about U-M benefits. Required Qualifications* PhD degree or equivalent in epidemiology, gerontology, sociology, or other relevant

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