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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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. Unsupervised machine learning approaches will be used to identifiy key dimensions of circadian rhythm associated with dementia subtypes. This requires a very good level in statistics and R programing as
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oxides, we will first develop and benchmark machine-learning interaction potentials of increasing complexity. Subsequently, we will deploy a combination of brute-force and rare-event sampling to isolate
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statistical / machine learning methods, pathway/network analysis or artificial intelligence approaches. Other requirements: The candidate should have a PhD or equivalent degree in bioinformatics, artificial
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generation of MOF water adsorbents with optimal indoor air humidity control performance by leveraging state-of- the-art high-throughput (HT) computational screening based on Machine-Learning Interatomic
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
-10346 Requirements Skills/Qualifications PhD in Computer Science, Machine Learning, Signal Processing, or a closely related field, completed or nearly completed at the start date. Strong background in
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-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection