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these stakeholders in terms of accountability and control of various types of risks (e.g., project, product, process, environmental, economic, or regulatory). This generally leads to a need for collaboration, mutual
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impactful, application-driven research. This position supports a strategic research project on full electric harbour craft microgrid modelling, onboard energy management systems (EMS), and hardware-in
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tasks. Key Competencies Integrates GIS, remote sensing, and environmental data for spatial modelling. Proficient in or able to learn ecosystem service software (e.g., InVEST, ARIES). Strong analytical
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Website https://uhw.msu.edu/health-and-wellbeing Summary of Health Risks TB and Human Tissue Bidding eligibility ends March 24, 2026, 11:55 PM Create a Job Match for Similar Jobs About Michigan State
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references Work Hours STANDARD 8-5 Description of End Date This position is funded for two years from date of hire with possible extension contingent upon funding renewal. Website https://cvm.msu.edu/ Remote
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to make a meaningful impact? Doctoral School of Microbiology and Environmental Science - Doctoral Positions (STEM CALL 2026) 174 Research Services and Career Development Working hours: 30 | Collective
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University and work in teams. Where to apply Website https://www.academictransfer.com/en/jobs/358493/assistant-professor/apply/ Requirements Specific Requirements you hold a PhD in Environmental Economics you
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the desire to make a meaningful impact? Doctoral School of Microbiology and Environmental Science - Doctoral Positions (STEM CALL 2026) 174 Research Services and Career Development Working hours: 30
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | 19 days ago
14 Mar 2026 Job Information Organisation/Company Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung Research Field Environmental science Researcher Profile Recognised
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools