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. Please include a description of one related deep learning model or framework (e.g., AlphaFold, ESM, Chai-1, Boltz-1, etc.) that you have used. Briefly describe what you used it for and tell us about
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learning algorithms (Deep learning, Reinforcement learning, etc.); Proficiency in written and spoken English - essential for data analysis and communication with stakeholders Excellent oral communication
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Job Purpose The Professional Officers Division (POD) houses a centralized pool of academic staff under the Professional Officers scheme. Professional Officers come with specialised and deep
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, Artificial Intelligence, Data Science, Computational Biology, Biomedical Engineering, or a related discipline. Strong research expertise in machine learning, deep learning, or computational modeling with
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vision principles. Familiarity with Python and at least one deep learning framework (e.g., PyTorch, TensorFlow, or Keras). Interest in research and willingness to learn and explore new concepts. Good
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[map ] Subject Areas: Mathematics, AI-based drug design and discovery, Bioinformatics/Protein Engineering/Single-cell Omics Data, Mathematical AI/Machine Learning/Deep Learning, and Computational
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: Essential criteria PhD qualified in Mathematics, Physics, Engineering or Computer science or near completion* Experience in language computer programming (Python) General experience in machine learning/deep
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to join our team at the CRSA to develop AI models, specifically deep learning approaches, to analyze and predict key climate variables such as precipitation and temperature which are essential
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simulations, transport/mixing in complex flows), active matter/biophysics or deep reinforcement learning, as well as a taste for interdisciplinary research and programming (Python). Environment. The successful
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involves a deep dive into biological systems using computational techniques. The candidate will help design and implement algorithms to analyze complex biological data (like high-throughput sequencing data