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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group
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Institut of Mathematics of Marseille | Marseille, Provence Alpes Cote d Azur | France | about 1 month ago
nonstationary models and algorithms for analyzing various biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential
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on two types of cultural heritage objects: medieval parchments and antique coins. PHOENIX aims to develop a methodology based on physicochemical characterizations capable of addressing common objectives
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optical medical devices. The works is aiming to develop optical devices and processing algorithms to guide neurosurgeons during the intraoperative neurofunctional assessment and connect these optical
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in the group optical medical devices. The works is aiming to develop optical devices and processing algorithms to guide surgeons during cancer surgery using fluorescence measurements. The post is based
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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. PyTorch). Experience analyzing high-dimensional data (biological or otherwise) or single-cell, bulk sequencing, or other biological data. Experience in algorithms and good software development practices
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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work
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Professor Daniel Paulusma from Durham University and Professor Vadim Lozin from the University of Warwick. The general aim of the project is to develop algorithmic meta-classifications, which state that any