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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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emulators of similar datasets (e.g. Gaussian Process methods by the project lead). These results will inform the IPCC AR7, and adaptation and mitigation policymaking by other global stakeholders. You will be
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European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs … How to apply Applications should include
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: Focus Data science and/or statistical methods development addressing questions of health, technology, housing, education, innovation and others impacting national and international urban communities
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rotation forestry towards continuous cover forestry methods is debated in Scandinavia as a way forward to increase biodiversity and climate resilience. This postdoc project will be based on empirical field
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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related discipline. The candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation
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quantitative methods and excited about discovering physical principles of biological organization. Minimum Requirements: PhD in a scientific disciplines, ideally Biology, Bioengineering, Physics or Math
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diversity of methods and data available to the discipline. We are further developing our core undergraduate programmes and will be recruiting world leading staff accordingly to ensure these programmes
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to IDRIS Experience in analyzing real data Strong programming skills Familiarity with statistical methods Excellent communication and writing skills City: Newark State: NJ Location: Rutgers University-Newark