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algorithms for for cache management and job scheduling in modern computing systems (such as LLMs). Analyze theoretical aspects of distributed systems, including optimization, scalability, and efficiency
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-of-the-art machine learning/deep learning models for RNA sequence design, structure prediction, and property optimization. Process, curate, and model high-throughput screening and genomics datasets
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learning, large-scale model optimization, and generalization. To explore scalable optimization methods for large-scale, distributed, and multi-node collaborative training. To conduct theoretical analysis
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key role in driving high-impact research, developing innovative objectives, and formulating proposals within cutting-edge fields, including Computer Vision, Digital Healthcare, AI Optimization, and
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. Contribute to research papers, technical reports, and presentations for internal reviews and external conferences or journals. Job Requirements: PhD degree in computer science or a related discipline. Good
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of efficient AI-for-Science systems, leveraging foundation models (including small language models) and parameter-efficient adaptation techniques such as LoRA, grounded in a strong understanding of optimization
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learning are preferred. Key Responsibilities: Strong candidates should take the lead of at least one of the following responsibilities: Soil organic carbon model development and optimization, focusing
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UiO/Anders Lien 15th August 2026 Languages English English English PhD Research Fellow in computer science/AI for energy informatics Apply for this job See advertisement About the position We invite
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English PhD Research Fellow in computer science/AI for energy informatics Apply for this job See advertisement About the position We invite applications for position as PhD Research Fellow in
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through the development of more effective diagnostic and therapeutic approaches. Qualifications and Experience · PhD in Bioinformatics, Computational Biology, Statistics, Genetics, Genomics, or a