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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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SQL databases and file repositories. We are now taking the next strategic step: developing ontologies and a dynamic knowledge graph to semantically link our internal data systems - and connect them
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market frameworks and business models for fair value distribution will be analysed. Responsibilities and qualifications Your primary research tasks will include: Develop and simulate coordinated control
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Job Description AI has begun to transform molecular discovery and design for proteins, DNA, RNA, small molecules and more. Yet many outstanding challenges in health and sustainability remain data
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computer science, mathematics, or a related field will be considered an asset. The position requires the ability to work independently as well as in collaboration with colleagues in a dynamic and international
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to apply machine learning techniques to a combination of experimental data and simulation results, aiming for faster and more accurate predictions. About us You will join an international and highly
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collaboration that covers all aspects of our research: theory and modeling, sample growth and fabrication, experiments and demonstrations. We have created a dynamic research environment of young and senior
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equivalent) in Allergology, Immunology, Bioinformatics, Biochemistry, Biomedical, Protein Chemistry, Molecular Biology or a related field as well as: Solid understanding of immunology and/or food allergy, and
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characterization aspect of the project, i.e. investigation of dynamics during catalyst activation and reaction by in-situ transmission electron microscopy. VISION is pioneering technology for visualizing catalytic
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qualifications we are looking for: Excellent knowledge and practical experience on current molecular microbiology methods Experience with genomic and transcriptomics data analysis is beneficial. Experience with