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Field
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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into **influence functions**, theoretical tools designed to quantify the impact of a sample on a machine learning model. These functions, defined through the derivative of model parameters or the loss function with
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experimental design. Collaborate with another postdoc in the NIH Center to use scientific machine learning (SciML) to automatically select mathematical models from data. Minimum Requirements: Ph.D. in applied
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addition to this basic research, FTRG is involved in large community-based prevention efforts in both military and civilian populations. These studies use the full spectrum of research methods, from intensive
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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of machine-learning models at catchment to regional scales. LanguagesENGLISHLevelExcellent Additional Information Work Location(s) Number of offers available2Company/InstituteUniversitat Politècnica de
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). The candidate should have hands-on experience developing state-of-the-art machine learning models, particularly deep neural networks (experience with graph neural networks is highly valued). Their background
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Mathematics/ Approximation Theory to be filled by the earliest possible starting date. The Chair of Applied Mathematics, headed by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning
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laboratory team is likewise highly recognized for its research in computer vision and neuro-inspired artificial learning. Both teams have been collaborating for four years on projects at the interface between