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: Postdoctoral Position Location: Taipei, Taipei, Taiwan Subject Areas: Physics / Biology , Biophysics , Chemistry , Computational physics , Condensed Matter Physics , Machine Learning , Nanotechnology
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. Mathematical techniques include qualitative and numerical analysis of deterministic and stochastic dynamical systems, optimal control, network models, and machine learning. Preference will be given to candidates
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regular basis with the experimental groups in the initiative. The position requires sound verbal and written communication skills in English. Swedish is not a requirement, but willingness to learn is
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to learn more about what the Bangor region has to offer. Qualifications: Required: Doctoral degree in engineering, environmental science, geoscience, or related field. Knowledge and experience in engineering
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 4 hours ago
skills and experience and interest in data analysis, data science, machine learning and process automation would be an advantage. Previous experience with XAS or other synchrotron-based techniques would be
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artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic
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compensation package. This tool takes into account all of the benefits that you are eligible for, including health insurance, retirement plans, and paid time off. To access this tool and learn more about the
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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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Online applications must be received before 11:59pm on: July 6, 2025 If a date is not listed above, review the Applicant Instructions below for more details. Available Title(s): 306-YN_FACULTY
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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible