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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 2 months ago
field A strong publication record in high-impact venues (NeurIPS, ICML, ICLR, AAAI, ACL, EMNLP, Nature/Science family, JAMA, Lancet Digital Health, or equivalent) Deep expertise in machine learning and/or
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CW and pulsed laser systems, spectrometers, high-resolution cameras, and delicate optical components are desirable Expertise in advanced data analysis techniques (Machine learning and Deep learning
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), it must be equiva-lent to a master in the Norwegian educational system Documented proficiency in scientific programming (e.g., Python) Documented proficiency in deep learning frameworks (e.g., PyTorch
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predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You will
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populations and biobanks for risk prediction, genetic discovery, and genomic medicine. Federated and transfer learning for distributed and privacy-preserving data integration. AI and Deep learning approaches
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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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, 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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fellowship program in cytopathology. The core responsibilities include performing superficial fine needle aspirations and on-site assessment of guided deep aspirates on both pediatric and adult patients
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for roughly 3% of global CO₂ emissions, and with international pressure to decarbonize hard-to-abate sectors, nuclear propulsion is emerging as a serious candidate for deep-sea and high-utilization vessels
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At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in