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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
students, and collaborate with AI faculty in vision, robotics, and machine learning across the department. Minimum Education and Experience Requirements Applicants should have, or expect to receive before
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geoscientific process models, as demonstrated by presentations, publications and/or repositories Expertise in applying Bayesian statistical methods, machine learning methods, or related statistical inference
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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(postdoc) Limited until: 31.10.2032 Reference no.: 6212 There are many good reasons to want to research and teach at the University of Vienna. And one is why around 7,700 academic staff members before you
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, pharmacological and chemogenetic experiments in rodents to delineate mechanisms underlying drug abuse. Conduct conditioned place preference, and learning and memory tasks, intracerebral infusions, and
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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools to the setup Create and validate reproducible automated workflows
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of reactive force field molecular simulations, supervised machine learning techniques and understanding of mass spectrometry techniques. The post is available for 3 years from 1 September 2026. If you are still