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-learning methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems
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contact us via our HR contact page external link . Knowledge security screening can be part of the selection procedures of academic staff. We do this, among other things, to prevent the unwanted transfer
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, the Museum contributes to the development and sharing of knowledge on geological and biological cultural and social diversity, on diversity. Unit description: UMR 208 PALOC ‘Local Heritage, Environment and
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related field. Demonstrated knowledge of Python or another major programming language for data analysis and familiarity with machine learning approaches for data analysis. Knowledge of Machine Learning
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activities utilizing an advanced level of knowledge within their perspective field. They will also contribute to writing proposals and papers, while helping to maintain laboratory equipment, and may contribute
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the biomass, assess treatment performance over time, and investigate options for harvesting and characterizing metal-enriched algal biomass. The aim is to provide the mechanistic and operational knowledge
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theory - Experience in scientific writing (articles, reports) - Very good communication skills (written and oral) in French and English Useful skills: - Knowledge of biological invasions
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programming. • Proven experience in deep learning (PyTorch or TensorFlow). • Previous experience with high-dimensional biological data and knowledge in (epi)genomics will be appreciated. • The ability to work
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this space. Skills, Experience & Qualifications Needed PhD in a relevant biological science, or equivalent. Knowledge of relevant research techniques and methodologies. Good communication skills, ability
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manuscripts, reports, knowledge mobilization products, and conference presentations; contributing to grant development (e.g. preparation of large-scale national funding applications). perform administrative and