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are seeking a highly motivated PhD candidate to develop efficient on-device generative AI systems based on large language models (LLMs). The project focuses on creating compact, low-latency, and energy
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to accommodate their own particular input setup and deciding the best modelling practice. This PhD project will aim at automatic solution development, supporting flexible input setups and addressing in one
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interfacing of the sensors. The PhD candidate will work at the Integrated Devices and Systems (IDS) group within the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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coincide, potentially exacerbating the situation. However, SAI’s ability to prevent full AMOC collapse has not yet been studied in models. In this interdisciplinary PhD project, you will address
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including interdisciplinary communication and collaboration. You will also be offered
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PhD in innovative stable isotope measurements of methane and its precursors Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 15