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at the forefront of the research field and advance it through experimental work, molecular annotation strategies and data analysis. You will work with state-of-the art instrumentation and have the opportunity
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“Quantitative predictions of protein – DNA interactions from high-throughput biophysical binding data”. Sequence specific binding and recognition between transcription factors and DNA control gene expression at
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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Preferred Qualifications: Prior exposure to deep learning frameworks (e.g., TensorFlow or PyTorch) and an understanding of state-of-the-art data preprocessing techniques. Demonstrated experience in
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focuses on the development of novel fluorinated amino acids as a 19F-NMR probe to study protein dynamics and protein-ligand interaction to facilitate drug discovery. It is financed by SciLifeLab, and hence
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biology of infection covers research that will transform our understanding of pathogens, their interactions with hosts and the environment, and how they are transmitted through populations. Research will