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mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time-lapse data Proven programming expertise in
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(Hourly Rate). To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html Department
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for the PhD admission is available at TalTech´s web-page: https://taltech.ee/en/phd-admission The following application documents should be sent to tarmo.soomere@taltech.ee CV Motivation letter Degree
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will also involve service engagement within the department, college, and/or university, including contributing to assessment of student learning outcomes, assessment of curriculum, participation in
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that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement. The salary range for this position is $31.53 - $39.63 (Hourly Rate). To learn
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, or similar) will be valued; 9) Experience in machine learning techniques applied to materials science or process engineering (regression, classification, optimization, predictive models) will be valued; 10
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device health status through condition monitoring. AI techniques such as machine learning will be used to optimise gate driver performance and to map gate drive signal attributes to power device health
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, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary The Rutgers School of Nursing invites applications for a faculty position that will be jointly appointed with Rutgers
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally