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Vidacs to confront optimal transportation approaches to machine learning methods.• One at UNIBO in Bologna for 12 months with prof. Daniel Reomndini to learn and apply techniques of manifold learning
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detection systems for ICS while considering advanced threats that usually have low activity profiles. We will leverage Machine Learning (ML) techniques, in particular, deep learning algorithms over Graph
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French National Institute for Agriculture, Food, and Environment (INRAE), Jouy-en-Josas | France | 25 days ago
developed by MaIAGE partners (e.g. Omnicrobe application*, Ontobiotope ontology*, extraction workflow). Expected results:The PhD student will design and evaluate original machine-learning-based methods
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physics or computer science, with a solid background in AI/machine learning techniques. A background in plasma transport phenomena as well as an experience with data analysis, statistical methods, and
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Proportion of work : Full time Workplace : Institut de Science et d'Ingénierie Supramoléculaires (ISIS) – Centre Européen de Sciences Quantiques (CESQ) Desired level of education : PhD or equivalent
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-based drug design Machine learning Molecular dynamics HTS data and SAR analysis Communicate with project teams and other departments: Interact with other experts in the project in various experimental
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Proportion of work : Full time Workplace : Institut de Science et d'Ingénierie Supramoléculaires (ISIS) – Centre Européen de Sciences Quantiques (CESQ) Desired level of education : PhD or equivalent
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student will develop the cyber section of CIENS' research and teaching activities. WORKING ENVIRONMENT AND CONTEXT With a PhD in Human and Social Sciences (law, philosophy, political science, strategic
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communication skills and team spirit, and an ability to work in autonomy are essential. Fluent English both spoken and written is required. Degree: PhD level in computer science, machine learning, bioinformatics
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Ecole Nationale Supérieure des Mines de Saint Etienne | Saint Etienne, Rhone Alpes | France | about 1 month ago
ENFIELD. Mines Saint-Étienne conducts research on sustainable AI from the angle of computational cost of machine learning and lifecycle assessment of AI systems. Scientific challenges: Language models and