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for Biorefinery, Bio-based Materials and Functional Printing) in Grenoble (Gières Campus) within the MatBio team (Multi-scale biobased materials). The LGP2 is a mixed research unit (UMR 5518) associating the CNRS
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sustainable and optimized processes for vanadium extraction and purification, with the goal of enabling large-scale redox flow battery deployment for energy storage. Scope of Work The successful candidate will
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existing hydrodynamic code to simulate experiments from the literature, implement and improve multi-phase behaviour laws to optimise their predictive capabilities, and carry out new laser shock experiments
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at the scale of biobanks. The position will focus on methodological and applied work in either one of the two broad, complementary areas: High-dimensional causal mediation and inference using AI methods
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candidate will be encouraged to independently explore large-scale omics datasets (e.g., bulk and single-cell RNA-seq, spatial transcriptomics, proteomics) to identify and prioritize novel biomarker
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large, multi-site human cohorts in Europe. The successful candidate will oversee the collection, processing and analysis of microbiome samples, ensuring harmonised protocols, high-quality data generation
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, enabling the interpretation of multi-stimuli optical responses of the developed materials and ensuring their effective use within the ML framework. Overall, this integrated approach will ensure a seamless
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large-scale speech and wearable data from participants in the GLAD Study cohort ( https://gladstudy.org.uk/ ). Using large language models (LLMs) and acoustic analytics, they will uncover patterns in
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of the candidate’s results (a scale of the evaluation: 0-3 points). Website for additional job details https://ibb.edu.pl/en/phd-studies/rekrutacja/ Work Location(s) Number of offers available1Company
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 days ago
1801P.01158.1.04, financed by national funds through FCT/MCTES Workplan: To develop a two-stage multi-scale vision-language model for the identification and classification of breast lesions in high