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be responsible for developing, automating and optimizing data acquisition and analysis workflows for experimental datasets. The candidate will work on the following tasks: Simulation and modeling
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. The project includes developing coarse-grained models, analysing membrane structure–performance relationships, and integrating simulation results with experimental observations. Experience or a strong interest
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related discipline. A passion for experimental work and capability to develop/apply mathematical modelling techniques will be particularly important for this project. Where to apply Website https
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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Assistant to support applied research at the intersection of healthcare, artificial intelligence, and data analysis The primary focus of this role will be large language model (LLMs) and other machine
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Details The aim of this project is to combine nanomechanical methods with modelling (i) to develop quantitative, predictive models for the behaviour of molecules in sliding contacts, and (ii) to understand
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in data analysis, mathematical modeling/computer simulation, and best practices in rigorous and reproducible science. The appointee will play a central role in developing, evaluating, and refining
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include data review and gap analysis, decomposition and simulation modelling using tools such as LEAP Ireland, and supporting the design, testing, and validation of policy-relevant indicators and sectoral
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» Cybernetics Engineering » Control engineering Engineering » Systems engineering Engineering » Simulation engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline
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" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time-limited positions may be eligible for all, some, or no benefits, based on the grant or project funding. South Carolina