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commercialization potential. The project focuses on next-generation batteries in three parallel research directions: extreme-temperature (high- or low-temperature) batteries, lithium- and/or sodium
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the consortium code base. Preference will be given to candidates with a strong publication record and proven experience in Python programming, source code versioning and management, machine and deep
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. Demonstrated experience with publications in top-tier journals and conferences. Proficiency in programming languages commonly used in deep learning such as Python and familiarity with frameworks like TensorFlow
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Engineering, or a closely related field. The candidate should be experienced with multiphase flow in porous media using FE, FV or FD methods, and should be proficient with a scientific programming language such
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mapping, or chromosome pairing studies. Familiarity with plant tissue culture and phenotyping techniques. Proficiency in programming languages such as Python, R, or Linux shell scripting. Interest in
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discipline, such as marine biogeochemistry, data science, nutrition epidemiology, environmental science, or related fields. Strong quantitative and programming skills (e.g., R and other statistical and
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! Qualifications PhD (completed or near completion) in Fisheries Economics, Environmental Economics, Resource Economics, or a closely related field. Strong quantitative and programming skills, with demonstrated