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multi-omic sequencing, network biology, and machine learning to identify actionable biomarkers and therapeutic vulnerabilities. The successful candidate will work at the interface of computational
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researchers and PhD students. The research groups conduct research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as
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strengths in experimental soft condensed matter physics or biophysics research within the department. Candidates with expertise in computational physics, including machine learning, applied to study soft
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; the upcoming Cryoscope pathfinder in Antarctica; the upcoming Roman Space Telescope (the RAPID PIT and RISE WFS teams are led by Caltech) Stellar astrometry and spectroscopy with Gaia and Euclid Machine learning
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., computational learning theory, expressiveness of transformers and other models, xAI, formal methods) or equivalent; willingness to conduct research on artificial intelligence/machine learning, combined with
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variety of affiliated hospitals, research centres, and sites, providing unparalleled opportunities to learn, discover and contribute in one's own way. UBC's Postdoctoral Fellows Office (PDFO) is committed
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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Assistant Professor in Marine Biology & Ecology - Biomedical Science or Quantitative Systems Ecology
ecologist working in coastal systems, who applies modern approaches in causal inference, experimental ecology, spatial modelling, and data science, including the use of machine learning to produce rigorous
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machine learning and network biology. Background in cancer research. Pay Range: $62,232.00 - $81,000.00 To apply visit https://academicjobsonline.org/ajo/jobs/31509 and submit a cover letter, full CV, and
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or equivalent Skills/Qualifications Technical Skills: Programming and integration of machine learning algorithms, reinforcement learning and symbolic planning in real robotic platforms. User modeling techniques