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using Machine Learning who has: strong experience in signal processing, machine learning or a related field a PhD (or near completion) in signal processing, machine learning or a related field experience
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: Overcoming Inequity in Embodied Learning in Danish Vocational Education and Beyond, funded by Independent Research Fund Denmark. This is a full-time (37 hours per week), fixed-term (24 months) postdoctoral
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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 12 days ago
conversion. Your profile PhD in electrochemistry, catalysis, surface science, physical chemistry, or a related field Excellent documented research record Experience working with flow cells, FTIR, as
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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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Job ID: 6217 Explore and teach at the University of Vienna, where over 7,700 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate about groundbreaking
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, Texas Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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quantitative microscopy. Ideal Candidate Qualifications: Candidates must have recently obtained (or will obtain before starting) a PhD from a biomedical research background. Experience in one or more areas of
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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framework 3) to develop a minimum viable digital platform prototype to demonstrate scalable CDT delivery. The successful candidate must be able to demonstrate at least one of the following: a PhD degree