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studies, surveys); Maintain current models and update them according to the new state of the art large LLMs; Analyze data and transform it into accessible visualizations and knowledge. As part of your
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targets. You will take a lead on development of computational approaches to integrate multi-omics data from patient samples, including DNA methylation, histone modifications, single-cell transcriptomics and
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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The Princeton University WET LAB (https://ren.princeton.edu/) is seeking a postdoctoral research associate(s) or more senior researcher(s) with expertise and interest in Large Language Models (LLM
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empirical methods, namely on the analysis of: Large-scale microdata sets, in particular, the excellent Danish micro-data; Experiments, both in the laboratory and the field; Other types of primary data like
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of Freiburg, founded in 1457, belongs to the best universities of Germany. Freiburg has a large international studen body and is located in the Black Forrest with a 30-minute drive to both Switzerland and
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presenting research at international scientific conferences. Experience working with small compounds and/or experimental drugs. Experience analyzing large data sets. After an overall assessment
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& Information Technology (CSIT). The Centre comprises approximately 50 people working on networks, security and systems research. CSIT is a large, research-focused school, participating in many major national and