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Field
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, proteomics, metabolomics, and computational modeling, fostering high-impact interdisciplinary research. Responsibilities: The successful candidate will work on projects, which will be involved in one or more
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, mathematics, computer science, engineering or a related discipline Required Other None Additional Preferred Experience working in one of the following areas: Machine learning/predictive modeling
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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line at the interface of nutrigenomics, clinical genomics, and toxicogenomics Design and apply bioinformatics workflows and predictive systems biology models Analyse multi-omics datasets from clinical
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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produced under conditions representative of rocket engines, for a selection of metals. After meticulous experimental characterization, the unique database obtained will be exploited to enhance the modeling
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a machine learning model (foundational model) to propose protocols of sequential induction of transcription factors to generate desired cell subtypes. The project will be conducted in close
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Ireland Pathways programme and will focus on the development of predictive computational models for advanced functional materials for electrochemical energy applications, with particular emphasis on polymer
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exploring the evolutionary trajectories of energetic frustration from ancestral to extant proteins, combining ancestral sequence reconstruction, structure prediction, and statistical energy models
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computational datasets of disordered materials based on density functional theory calculations and training machine learning models to accelerate the predictions. This work will involve collaboration with Assoc