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Organisation Job description We are looking for a PhD candidate in the group of Prof. A. J. Minnaard, who leads a natural product synthesis group at the Stratingh Institute for Chemistry (see
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smart materials. Building on the foundational work recognised by the 2016 Nobel Prize in Chemistry, MonaLisa aims to make groundbreaking discoveries in the design and functional control of molecular
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achieved consensus. The PRELIFE consortium brings together leading researchers from a wide spectrum of disciplines—including astronomy, biology, chemistry, computer science, earth and planetary sciences
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We are looking for a motivated PhD candidate for a project carried out under the supervision of Prof. Ben Feringa at the Stratingh Institute for Chemistry. The project is part of the EVOLVE
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consortium comes in. PRELIFE unites experts across a wide range of disciplines from astronomy, biology, chemistry, computer science, earth and planetary sciences, education, mathematics, to physics. Together
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PhD position - Modelling the emergence of information transfer in prebiotic self-replicating systems
consortium comes in. PRELIFE unites experts across a wide range of disciplines from astronomy, biology, chemistry, computer science, earth and planetary sciences, education, mathematics, to physics. Together
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determined candidates, who meet the following requirements: An MSc degree (or an equivalent university degree) in (Bio)chemistry, Biotechnology, Computational Chemistry, Synthetic Chemistry/Biology or a
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provide better therapeutic options for AML patients.Requested skills: We look for a candidate with a master’s degree in (bio)physics, (bio)chemistry or a related field, with a strong interest in molecular
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skilled in computational chemistry and data-driven approaches to develop new catalytic asymmetric reactions. World-leading industrial partners with a wide range of interests will provide advice on which
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academic research groups with expertise in experimental catalyst development and theoretical groups skilled in computational chemistry and data-driven approaches to develop new catalytic asymmetric reactions