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Machine Learning Bioinformatics The successful candidate will contribute to advancing state-of-the-art in data mining and machine learning research with applications in computational biology by: Developing
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the following ones. Exploration of active auditing techniques for large machine learning models, use of reinforcement learning, potential application to recommender systems. The PhD will mainly investigate
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posts,PHD Thesis Starting date: 30.10.2025 Job description: DESY Foundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of
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-agent reinforcement learning (MARL) framework for cyber-physical networked fault-tolerant control of renewable energy-fed smart grids under adversarial conditions [6]-[9]. Multiple autonomous agents will
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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team and be willing to learn from your co-workers and to share your knowledge and experience with them in return. Scientific curiosity and the ability to think independently are essential personal
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expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
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Your profile PhD applicants must hold a Master's degree in computer science, mathematics, or electrical engineering, with demonstrated strength in either practical implementation or theoretical foundations. Candidates should possess an exceptional academic record and a strong mathematical...
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in higher education and research, in and outside academia. This PhD fellowship is part of the newly established AI Centre for the Empowerment of Human Learning (AI LEARN) .Six national research centers