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diseases by uniting AI and nanotechnology Lead the bio-market via trans-disciplinary convergence in AI, nano-optics, and protein-structural biology Core Technologies: Neurobiology, Neuroscience on proteins
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sensing, signalling and memory, critically influences the disease onset and progression1. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is
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sensing, signalling and memory, critically influences the disease onset and progression1. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is
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students) aims to understand the bio/chemical basis of plant resilience and performance in challenging environments. The IPB offers excellent research facilities and state-of-the-art infrastructure
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qualifications at the time of hire. D octor in Philosophy (PhD) in Immunology, Cancer Biology, Molecular Biology, Biochemistry or related field in the bio-medical sciences. Experience in cell culture and basic
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 22 days ago
, or intrinsically disordered proteins. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular
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. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular (bio)physics, statistical
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, advanced manufacturing, and bio-signal acquisition, as well as experience working with biocompatible materials and miniaturized platforms for medical applications. They should be comfortable working
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We are seeking a highly motivated Research Associate to work on a Wellcome Trust–funded project using bio‑behavioural and data‑driven approaches to investigate emotion signalling mechanisms in both
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The role We are seeking a highly motivated Research Associate to work on a Wellcome Trust–funded project using bio‑behavioural and data‑driven approaches to investigate emotion signalling