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) and reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing
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to grant proposals, and present findings at international conferences. What you bring: PhD (or near completion) in Bioinformatics, Computational Biology, Data Science, Statistical Genomics, or related field
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experience in machine learning research and development, particularly with a specialisation in such areas as: digital forensics, computer vision, biometrics (face or voice recognition, etc.) and natural
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learning and cloud-based architecture skills to lead the fine-tuning/training, design, development, and integration of the AI components of the AiCT-Med platform. Candidates from diverse backgrounds in AI
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and Machine Learning tools and algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability
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for improved interpretability and generalization. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability to work collaboratively in interdisciplinary and cross
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(LLMs); Configure and optimize cloud computing solutions or on-premise infrastructures that ensure high availability and scalability; Implement tools for efficient resource management, such as GPU
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and integrate cloud computing solutions and/or robust and scalable on-premise environments. Framework Development for Learning Environments with LLMs:Create a modular and extensible framework
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. - Demonstrated ability to work with high-performance computing environments during academic training, with basic knowledge of cluster usage or cloud-based AI tools More Information Location: Kent Ridge Campus
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, toxicology, or pharmacology Understanding of biological pathways and their relationship to disease mechanisms or drug response Experience with cloud computing environments and large-scale data processing