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to reason about software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new
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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
in professional journals. Job Duties The Department of Pharmacology and Toxicology at ECU invites applicants for a full-time (12-month) research or tenure-track faculty position in Pharmacology
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locomotion. Apply machine learning and machine vision algorithms to track body and limb movements. Use biomechanical modeling to analyze walking data and fit locomotion models. Operate a force sensor to
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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Research Track -- Assistant or Associate Professor, Department of Medicine (Clinical and Translational Glycoscience Research Center) - Georgetown University Medical Center Georgetown University
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position is funded by multiple NIH projects, e.g., https://tinyurl.co m/ysxhmujvThe overall goal is to : (1) develop inference and dynamic prediction models using a wide variety of data, including clinical
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the optimisation strategies to enhance the performance of complex machine learning models such as deep learning model and large language model. Applicants need to have strong background and track records of research
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are seeking outstanding early-career researchers who meet the following criteria: Educational Background: Ph.D. degree from prestigious university. Research Excellence: Proven track record of impactful research
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Department: Premier Center Salary: Commensurate with experience Description: The University of Houston College of Pharmacy invites qualified applicants to apply for a full-time, non-tenure track
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. Bonus lectures can be picked by the students depending on their interests and project-specific requirements. Students can deepen their knowledge about selected topics (e.g. Bayesian Statistics, HMMs, AI