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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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advanced, independent, or collaborative research, aiming for high-impact publications of scholarly merit. Simultaneously, the researcher will teach up to three courses per year, distributed over three
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performance with classical methods. Qualifications PhD in Physics, Computer Science, Applied Mathematics, or related fields. Strong background in at least one of the following: machine learning, quantum
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work is studying how undergraduate STEM courses can be tailored to meet the needs of all learners. Current projects involve studying STEM instructor perceptions of student-centered learning as
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, reinforcement learning, probabilistic modeling, and language-guided autonomy. Core Responsibilities: Conduct independent and collaborative research aligned with the themes above Mentor PhD and MS students Lead
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the research team in the area of Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine
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imaging datasets and advanced machine learning approaches to identify novel imaging markers of mental health disorders and cognitive function; 2) developing robust MRI-based acquisition, image
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learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in porous materials Develop novel machine learning model for predicting
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, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial