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SPECIFICS Postdoctoral Scholar – Public Health Sciences Postdoctoral Scholar of Machine Learning and Statistical Genomics Description: The Department of Public Health Sciences is seeking postdoc scholars
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and development of perception stacks for autonomous mobile systems in general in any field Machine learning/deep learning experience applied to perception and any experience with deep Learning
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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researchers working on hyperspectral imaging, radiative transfer modelling, machine learning, agronomy, and plant genetics. You will also work with HYDRA-EO partners in Netherlands, Spain and Italy
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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FieldBiological sciencesEducation LevelPhD or equivalent Specific Requirements PhD in Physics, Computational Biology, Bioinformatics, or equivalent. Knowledge of biophysics, statistical physics, machine learning
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inference and statistics; computer vision and novel applications of machine learning.Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is
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. Experience with machine learning is highly preferred. Ability to work independently and as part of a team. Key Requirements for PhD: Hold a Bachelor's degree with outstanding performance in Physics or related
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online databases or interactive websites. Learning Objectives: TUnder the guidance of a mentor, the participant will learn techniques in genomic epidemiology and machine learning to quantify drivers of IAV