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Field
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Sciences, who develop, manage, and refine machine learning techniques for identifying copyists; Participation in the dissemination of research results through presentations and publications; Data management
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 4 days ago
analysis platforms integrating AI and machine learning pipelines Coding skills in Python or R for data processing and visualization is an asset Fluency in English (spoken and written) Strong scientific
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(s). Knowledge of pulse generators, oscilloscopes, multimeters, power supplies, diode lasers, telescopes, cameras, range finders, lathes, milling machines, 3D printers, band saws. Salary: Compensation
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to scholarly peer-reviewed publications. Opportunities exist for the selected applicant to mentor students and to develop learning opportunities (courses, workshops, etc.) for the UK earth science community. The
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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analyzing urban data (traffic, energy consumption, environment). Strong skills in integrating IoT devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence
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-based knowledge with machine learning. You will work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop and implement surrogate and hybrid modelling
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: 12 September 2025 Apply now Are you a data scientist interested in designing and implementing process-informed machine learning and uncertainties quantification methods? Join us as a postdoc and work
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biology, and medicinal chemistry to uncover cancer-specific vulnerabilities and design therapeutics that restore apoptotic sensitivity. Learn more about our research: https://manoszax28.wixsite.com
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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships