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Field
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models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning
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A confluence of technological milestones in detector, computation and machine learning development, both globally and within the NRC, makes high-speed non-linear wavefront sensing for Astronomy
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to advancing machine learning in biomedicine. The Program focuses on developing and applying cutting-edge AI approaches to address key challenges in molecular biology, clinical research, and translational
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the methods to innovations in close collaboration with Aker BP and/or Equinor. The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine Learning, Department
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/HCI: PhD in Computer Science, Human-Computer Interaction, Information Science, or related computational fields with expertise in machine learning, natural language processing, human-AI interaction
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 1 day ago
engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal Application Deadline 16 Dec 2025 - 23:59 (Europe/Lisbon) Type of Contract Not Applicable Job Status Not
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acquired from the field survey Develop machine learning models for prediction and recommendation Job Requirements: Preferably PhD in Computer Science or related field. Expertise in computer programming
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for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in
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We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean processes. The role is part of PRECISE: Prediction of Climate Change and
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date to be determined. Basic Qualifications A PhD related to programming languages by the start date. Experience in machine learning and formal verification. Individuals with a demonstrated track record