421 computer-programmer-"IMPRS-ML"-"IMPRS-ML" Postdoctoral positions in United Kingdom
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of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse single-cell modalities, focusing on gene
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group at meetings. You will also have a strong publication record in a related field, and possess sufficient specialist knowledge in the discipline to work within established research programmes. You will
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. Computing time is available on our local cluster and on the Vienna Scientific Cluster (VSC), a supercomputer shared by Austria's major universities. We focus on the development of methods to solve the many
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research initiative funded by ARIA, titled Aggregating Safety Preferences for AI Systems: A Social Choice Approach. The project operates at the interface of AI safety and computational social choice, and
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will have or be close to the completion of a PhD in Neuroscience, Psychology or a closely related discipline. With in-depth knowledge of cognitive and computational neuroscience including motivation
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) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research activities and a wide-ranging portfolio of education programmes. Celebrating diversity and
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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We are recruiting a postdoctoral research scientist to lead virus evolution and bioinformatic data analysis for our program on wastewater surveillance for pandemic pathogens. The world has never
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly