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at NTU are looking for a Research Fellow (RF) to carry out research in probabilistic machine learning and GenAI, by exploring cutting-edge approaches such as sequence model design, continual learning
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on the candidate’s experience and interests, research activities may include: Designing and conducting studies using genetically engineered, lineage-tracing, carcinogen-associated, and other human-relevant mouse
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for Science, and scientific discovery by advancing our understanding of interpretable machine learning models and their practical applications in real-world domains such as healthcare and science. Key
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project “Interpretable and Automated Cryptanalysis for Tailor-Made Cryptographic Design”, the school is looking to recruit one research fellow on cryptography and/or machine learning. Key Responsibilities
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project “Interpretable and Automated Cryptanalysis for Tailor-Made Cryptographic Design”, the school is looking to recruit one research fellow on cryptography and/or machine learning. Key Responsibilities
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the design of smarter diagnostics and effective treatments. The team aim to understand the fundamental biological processes involved in dementia at a molecular level – and to use that knowledge
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the design of smarter diagnostics and effective treatments. The team aim to understand the fundamental biological processes involved in dementia at a molecular level – and to use that knowledge
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of table grape breeding lines to gray mold caused by Botrytis cinerea. Develop skills in designing and implementing scalable, high-throughput phenotyping methods to assess disease susceptibility. Learn
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reactions. Experience applying Machine Learning to optimise and guide iterative laboratory experiments. Experience of oligonucleotide design and of adapting an amplification method to new target sequences
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field. Prior experience or strong interest in tumor immunology and/or cancer metabolism is highly desirable. Demonstrated ability to independently design, execute, and interpret complex in vitro and in