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, including uncertainty estimation, risk-aware prediction, and data-efficient learning - Continual, transfer, and meta-learning, with emphasis on sim-to-real and real-to-sim generalization - Applied machine
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interdisciplinary team spanning statistics, machine learning, genetics, and population health. You will work closely with collaborators at the Nuffield Department of Population Health (NDPH), the Big Data Institute
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23 Mar 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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. Teaching skills. Additional assessment criteria: A strong ability to develop and conduct high-quality research independently. Experience using deep learning methods and computer vision with biological data
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Intelligence and machine-learning approaches and emerging digital technologies such as non-contact sensors, smartphones, and computer tablets. This theme could also include research in data analytics and
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deploy machine learning and deep learning models (transformers, large language models) for immunological data (biological sequences, single-cell data, and protein structures, virtual drug screening) Use
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team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In addition to their research work, candidates assist and
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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knowledge of power system security and machine learning being crucial. The Associate will primarily work alongside National Grid engineers to integrate the machine learning backend of the intrusion detection