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. · Experience in collaborations with experimental organic and biocatalysis research groups. · Experience in using machine learning tools in chemical research. · Expertise in using a variety of
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members across electrical engineering, earth science, signal processing, and machine learning to ensure methodological rigor and practical relevance. Qualifications: -Ph.D. in Electrical Engineering
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to earn associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more
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Location Indianapolis Position Summary Are you passionate about genomics, big data, drug discovery, and AI/machine learning? Interested in advancing cutting-edge multi-omics research to explore genetic and
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networks; experience in applying machine learning models and processing imagery from UAS and satellite platforms. Other Requirements: Willingness to work irregular hours and in occasionally adverse weather
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, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations to biomolecular systems is a plus but not required. Applicants
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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, little traffic, and a reasonable cost of living make the greater Bangor area a wonderful place to live. Visit the Maine Office of Tourism to learn more about what the Bangor region has to offer
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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, California 95616, United States of America [map ] Subject Areas: Physics / Astronomy , Astrophysics Computational , Machine Learning Salary Range: Starting at $71,491/year or higher depending on experience