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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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The postdoc’s work will involve research within dynamical systems theory and network theory, with applications in mathematical modeling in neuroscience and in machine learning. In addition, a smaller amount of
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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project primarily focusing on work packages 2 and 3. The post holder should be educated to PhD standard or be near completion (or equivalent) or have suitable experience working in education in a teaching
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16 Mar 2026 Job Information Organisation/Company Université de Haute-Alsace Department IS2M Research Field Chemistry Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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data (HRMS) used for non-target analysis. The projects aims to develop a combination of supervised and unsupervise machine learning stragaties for pinpointing chemicals that have high toxicity
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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. Joerg Hoffmann at University of Saarland. 2) 1-2 PhD students working with Prof. Hendrik Blockeel and/or Prof. Jesse Davis on the topic of developing novel approaches for learning, compressing, and
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family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Equal Opportunity Employer: Duke is an Equal Opportunity Employer committed to providing
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, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation