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, tissue sections, RNA/DNA, tabular data) for predictive modelling using software such as Python Documented experience of neural networks, image processing, deep learning algorithms, and data visualization
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(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
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integrates neuroimaging, sleep measurement, digital phenotyping, electronic health record (EHR) data, and deep clinical phenotyping to identify predictors of symptom trajectories and functional outcomes in
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required Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow) Experience with unstructured
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the research activities entrusted to the officer take place: This ANR project lies at the interface between statistical learning (mainly deep learning) and combinatorial optimization (mainly stochastic and
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in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL) methods. Demonstrated proficiency in
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biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical, recurrent, or developmentally inspired models
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recombinant minibinders for migraine-associated receptors. The project aims to advance deep learning–based molecular generation and structure-guided design for therapeutic innovation. We seek a highly motivated
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techniques and genomic data analysis. Background in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL
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. Demonstrated experience in either of the following areas (a) data science, (b) theoretical nuclear reaction models and/or (c) deep learning-based machine learning and applications of artificial intelligence