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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 1 month ago
of (a) (young) stellar clusters, (b) molecular gas and dust, or (c) star-forming sites (e.g. HII regions) in gas-rich galaxy centers. The work will encompass all aspects from data reduction to their in
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experience in life cycle assessment (LCA) and related tools for managing large data sets to evaluate natural resources needed to advance emerging technologies. The candidate will lead their primary project and
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required. Qualifications Required Education and Experience: Appropriate PhD in neuroscience, neurophysiology, or a related field. Preferred Qualifications: Expertise in software /data analysis such as
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outputs will inform work undertaken in the group in several large collaborative grants and application areas, including cultural heritage, enterprise data management, and legal compliance. The ideal
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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to the ongoing research in Prof. Marcotti’s laboratory by designing, developing and performing experiments, data analysis and disseminating the findings by writing articles and by presenting findings
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you will be offered an 18 month fixed term contract. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified
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role in technology improvements that will power the novel field-cage-integrated large-area photon detectors proposed for DUNE Phase 2. In addition, the successful candidate will be involved in
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Full-Time, Fixed-Term (36 months) Salary is £41,945 to £48,003 pro-rata per annum (including London Allowance) We are looking for a highly motivated early career researcher with a PhD (or near
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of metabolic states in retinal ganglion cells; spatial transcriptomic and correlated metabolic analysis of retinal ganglion cells; treatment of retinal ganglion cells in models of degeneration; data collection