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landscape constrains or enables discovery. The project draws on tools from topological data analysis (e.g., persistent homology, Euler characteristic curves, discrete curvature), machine learning (e.g
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non-target screening. Evaluation of obtained data and their statistical analysis. Elaboration of reports and communication with project/contract founders. Participation in preparation of proposals
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PhD Studentship: Green vs. Non-Green Innovation: The Role of Regulatory Policies and Market Dynamics
and financial constraints influence firms’ choices between green and non-green innovation, using theoretical models and firm-level data to assess whether environmental policies stimulate or hinder
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language of this project is English, and the candidate should be proficient in written and spoken English (also at teaching level). Requirements are listed here: https://set.kuleuven.be/phd/applicants
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detailed information on the admission criteria please see the PhD Regulations and the relevant PhD programme description . The applicant must document expertise and interest in the research subject. This
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analysis The candidate will also have a PhD in a relevant biological subject or due to complete within 6 months. This is a three-year training and development position suitable for you if you have recently
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. The project’s PI is Associate Professor Iselin Åsedotter Strønen. For more information about the project, see https://www4.uib.no/en/research/research-projects/invisible-women-of-the-sea-gendering-fishery
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technology, computer science, data management and data analysis, or at the intersections of any of these fields. The school complements this with an individually tailored course program for both physicists and
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: https://genomikadlapolski.pl/ ." We are seeking an ambitious individual to join the Laboratory of Genomics IBCH PAS and engage in the work of the G4PL project team, related to the analysis of genomic data
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. This PhD project wil combined longer-term monitoring data and new sampling campaigns for field measurements and sample collection to improve our quantitative understanding of carbon fluxes in the Congo Basin