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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
Machine Learning (DM3L) Doctoral Candidate in computer vision and machine learning for developing novel deep learning methods for satellite-based tracking of global CO2 and NOX emissions of point sources 80
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of industrial high-temperature processes with potential for negative carbon emissions. PhD student in the field of numerical simulation of plasma-based methane decomposition Your tasks Setup of Computational
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of Computational Fluid Dynamics CFD environment and simulations including: - Computation of the microwave field, Coupling of the microwave field with the plasma - Computation of elementary ionization, recombination
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12 Nov 2025 Job Information Organisation/Company ETH Zürich Research Field Computer science » Other Researcher Profile First Stage Researcher (R1) Country Switzerland Application Deadline 9 Feb 2026
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12 Dec 2025 Job Information Organisation/Company University of Basel Research Field Biological sciences » Biology Computer science » Other Mathematics » Statistics Neurosciences » Neurology
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Your position With your application you agree to our terms of participation . In principle, attendance is required at all program elements. Failure to attend may result in exclusion from the program
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related subject. Excellent communication skills in English, both oral and in writing. Strong interest in Materials Science and the application and development of advanced computational methods. Excellent
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. The candidate should have a strong background in computational biology or a related field. They will: Work closely with the clinical partner to understand the unmet clinical needs. Integrate the existing datasets
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matter physics, and quantum computing. You will dive deep into the realms of theoretical and computational physics with a focus on the development of algorithms and large-scale numerical simulations. Your
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security, privacy-preserving, and efficient computational methods to AI for genetic healthcare. Start: April 2026. Duration: 4 years (48 months).