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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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-like molecules (Fragment-Based Drug Discovery) has strongly modified the generation of therapeutic compounds1. The method consists in identifying small organic compounds (fragment hits) that bind
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for geometric PDEs, in particular for fluid problems posed on surfaces. Both theoretical analysis of numerical methods and code development. Job requirements: PhD in mathematics or applied mathematics, experience
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, engineering, applied mathematics, physics, or another STEM discipline. · Demonstrated experience with mathematical and numerical optimization methods, including, but not restricted to, geometry or shape
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Numerical relativity, machine learning Where to apply
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datasets (e.g. ground-based radar measurements and weather station data) Contribute to the development and application of numerical models Assess uncertainties for future sea-level projections Publish
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mechanics and materials mechanics - Strong interest in multiscale and multiphysics modeling - Knowledge of numerical methods and finite element analysis - Interest in hybrid physics–data approaches and
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the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology, including advanced imaging and related analysis Experience in the performance of high pressure
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fields: Material Science, thermal simulation, Metallurgy, Solidification of alloys,... School - Location: Centrale Lille Institute Laboratory: LaMcube Web site: http://lamcube.univ-lille.fr/ Name of
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water models for accurate and efficient simulation of free-surface flows. This includes model derivation, model analysis, and development and implementation of numerical methods. For more information, see