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Type: Fixed Term Project Overview We are seeking an outstanding and highly motivated Research Fellow (PhD) or Research Engineer (Master's degree) to join an exciting research project on Artificial
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methods, build and evaluate computer vision and machine learning algorithms empirically. Author research articles at an international level for peer-reviewed conferences. Engineer software based on the
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on research activities involving data analytics, computational modelling, machine learning, and optimisation. The role offers opportunities to contribute to research publications, technical
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- Epigenomics, Machine Learning & 3D Genome Biology Employer NYU Langone Health, Skok Lab Location New York City, New York (US) Salary Postdoc: $70,000+ annually, plus benefits; Senior Computational Biologist
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a degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. • Knowledge of machine learning, pytorch, huggingface etc... • Knowledge of
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mathmatical modeling. The candidate should also have a PhD or other advanced degree in a food or engineering related field. Knowledge of food formulation, sensory analysis, extrusion technology, machine learning, and rheology will be advantageous. Apply Now Job Alerts Link
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-scale projects is highly preferred. Familiarity with finance management, budget tracking, procurement, or grant administration will be an added advantage. Experience in areas such as Machine Learning
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UC Berkeley, Bakar Institute of Digital Materials for the Planet | Berkeley, California | United States | about 6 hours ago
Job Details At BIDMaP (Bakar Institute of Digital Materials for the Planet) UC Berkeley, researchers are combining AI, machine learning, and data science with the physical sciences to confront climate
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. Requirements: PhD in AI, Computer Science, Machine Learning, NLP, or a related discipline; or a Master’s degree with substantial applied research experience. 2-4 years hands-on experience with LLM
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NVIDIA Isaac Sim, Isaac Lab, Gazebo, or MuJoCo. Familiarity with humanoid robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning