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psychology A successfully completed scientific university degree in psychology Accurate working and strong team spirit Confident handling of large, longitudinal data sets Competent use of statistics and data
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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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the gastrointestinal system. This large-scale project, with partners at the LSB and the IUF in Düsseldorf (Leibniz Research Institute for Environmental Medicine), combines cellular and molecular biology, sensory science
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lines; generation of samples for proteomics analysis Data integration and analysis, including transcriptomic, proteomic and library screen data Target validation by CRISPR-Cas9 knockouts in primary AMLs
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
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) for different scientific applications, including simulations, large-scale data analyses and AI. This will involve designing test protocols, building test benches to track power and energy usage, and running
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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or unethical responses, can be manipulated into producing them when provided with a large enough number of well-crafted “in-context” examples. This raises critical questions: Why do AI models adapt so
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opportunity for a motivated scientist to unpick the impact of host factors on tumour structure. To lead this research as a doctoral student you will be passionate about using large-scale data to address
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the