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& Computer Science of the Eindhoven University of Technology in the field of “Geometric Learning for Image Analysis”.The two year postdoc position is part of VICI Project (VI.C. 202-031, PI: R.Duits) and will
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their team. The work will be jointly supervised by Professor Helen Byrne (Mathematical Institute, MI), Professor Simon Leedham (NDM), Dr Joshua Moore (MI) and Dr Eoghan Mulholland (NDM). Colorectal Cancer
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on performance and project needs. Qualifications • For Doctoral Candidates: Master’s degree in Mathematics. • For Postdoctoral Researchers: Ph.D. in Mathematics, ideally with a background in one or more of the
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Contribute to the preparation of scientific and technical reports. Develop and apply methodologies based on Density Functional Theory (DFT) to complex systems. Support simulation tasks and results analysis
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background and expertise in one or more of the following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural
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, including Spatial Transcriptomics and Multiplex Immunofluorescence platforms, for validation and calibration of mathematical models. You will also develop skills in mathematical modelling and spatial analysis
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modelling, simulation, and data analysis, applied first and foremost to the field of platelet biology and haemostasis. The postholder will play a key role in a project that will develop novel computational
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, Functional Analysis, Calculus of Variations and Optimal Control, Optimization, Mathematical Biosciences and Quantum Biology. Some of the current research projects in Applied Mathematics include laser ablation
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analysis, multi-omics analysis, differential analysis, machine learning methods. Definition of tasks to be performed: Fixed-term contract essential to carry out the bioinformatics part of the project
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or observational cosmology -ML architecture design and deployment experience -High-performance computing and large-scale data analysis -Background in neural density estimation or advanced ML techniques Position