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https://www.jobbnorge.no/en/available-jobs/job/298131/phd-candidate-in-spectral… Requirements Research FieldComputer scienceEducation LevelMaster Degree or equivalent Additional Information Work Location
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2026. Area of specialization within the field of Sustainability is open, but the candidate must be able to teach a range of lower and upper-level courses in service to innovative interdisciplinary B.A
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
(as machine learning techniques, etc.). Personal characteristics In the evaluation of which candidate is best qualified for the PhD position, emphasis will be placed on education, experience and
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inequalities and Sobolev-type spaces (with Hytönen and/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic
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/machine-learning-for-integrative-genomics/ The HUB : https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/ Degree : PhD in computer science, computational biology, bioinformatics
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to develop new methods, for example using machine learning. have a proven track record of independent research funding and high quality publications. have at least 5 years of post-PhD work experience
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: Doctorat de l'Université Grenoble Alpes PHD Country: France Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/136951 Requirements Specific Requirements With a Master degree, or
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), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine
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and machine learning techniques for the design of superconducting qubits, one of the leading qubit modalities used in today’s quantum computers. The optimal design of superconducting qubits is a highly