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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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, or similar languages Background in machine learning or deep learning methods Knowledge of genomics, transcriptomics, evolutionary biology, and plant biology is an advantage Familiarity with large biological
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Sensing (DAS) data processing and compression using ML Physics-driven machine learning for geophysical modeling and inversion Thus, the candidate is expected to have or about to have a PhD in a relevant
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initiative on Agentic AI for Scientific Discovery. This project aims to solve a grand challenge in modern AI: developing a deep research assistant capable of accelerating R&D workflows and operations in
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, simulation, and data-driven methods to support secure, reliable, affordable, and sustainable power systems under deep decarbonisation, increasing renewable uncertainty, and the growing participation
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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to Apply To be considered for this position, apply online, please submit your curriculum vitae and respond to the selection criteria below, attaching your response as a separate document. Essential A PhD in
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try again. UiO/Anders Lien 3rd July 2026 Languages English English English PhD Research Fellow in Active Learning for Arctic observing systems Apply for this job See advertisement About the position
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Schemes of Service: Research Division: Food, Chemical and Biotechnology Employment Type: Fixed Term As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications