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with teaching or research interests in: Algorithms Science of Programming Computer Vision Machine Learning Qualifications Applicants must have: A Ph.D. in Computer Science or a closely related field by
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records. Support adherence to institutional, sponsor, and regulatory requirements for human subjects research. Technical Responsibilities Validate and verify research algorithms, analytical methods, and
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, TensorFlow, or JAX) Experience with photonic design techniques and global optimisation algorithms (Genetic Algorithms, Particle Swarm, Gradient Descent) Experience implementing deep learning architectures
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with the PI in the development of analytical strategies to achieve the laboratory goals, including optimization of current algorithms used to determine transcription factor binding dynamics, pseudotiming
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
world. Position Summary The postdoctoral researcher will conduct advanced research in artificial intelligence (AI) and machine learning, with a focus on developing novel algorithms and systems. The position offers
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algorithms; identifies and resolves a wide range of issues/software bugs. Demonstrates good judgment in selecting methods and techniques for obtaining solutions. Operates independently. The incumbent will
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, and computer dose algorithms. Knowledge of treatment planning computers, both software and hardware, linear accelerators, including MLC’s, and imaging devices. Knowledge of treatment planning
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Using Machine Learning Algorithms (Plasmon-2Detect), ref. COMPETE2030-FEDER-00714300, number of the project - 16004, financed by the European Regional Development Fund (ERDF), with a view to the
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). AI Integration Upskilling: Prior experience teaching students how to ethically navigate AI-driven Applicant Tracking Systems (ATS), optimize profiles for digital algorithmic screening, and utilize
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(http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts