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) therapies for melanoma. This position offers a unique opportunity to work at the intersection of cutting-edge cancer immunotherapy and advanced computational biology. Position Overview: • Full-time
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 19 hours ago
. Application Deadline 7/29/2025 11:59:00 PM Eastern Time Zone Description The U.S. Department of Energy (DOE) Science, Technology and Policy Program (DOE-STP) is designed to provide opportunities for students
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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, viral tools, advanced bioinformatics, and statistical modeling to decode the complex molecular mechanisms that shape human vision. By leveraging high-dimensional data and cutting-edge computational
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to artificial intelligence (AI) (e.g. computer science, engineering, Statistics, and mathematics etc.) The post is available for 30 months, starting on 1 September 2025. If you are still awaiting your PhD to be
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previous research experience (computational and experimental) in the broad area of Nonlinear Mechanics. Applicants must have received a Ph.D. in Mechanical Engineering, or any closely-related field
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Processes and Materials group within the department of chemical engineering of the Faculty of Science and Technology at the University of Twente (The Netherlands). You are encouraged to visit the different
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Grade 6 Research Assistant Essential Criteria 1. A Master’s level degree (or equivalent experience) in Electrical Engineering, Energy Systems, Control Engineering, Computer Science, Artificial
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, or Chemical Engineering with a focus on resource recovery or battery materials. Research experience in metal recovery from slags or mineral concentrates, including both experimental and computational