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implementation Reference code: 50144551_2 Commencement date: 01.09.2025 Work location: Hamburg Application deadline: 13.07.2025 The Climate Service Center Germany (GERICS), a scientific organizational entity of
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within this project include: Extending DeepRVAT towards non-coding genetic variation Applying DeepRVAT to population-scale single-cell readouts Integrating population data with experimental perturbation
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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the proposed research fields. The group consists of approximately 17 members at different levels of seniority. Salary is paid according to German TV-L (salary agreement for public service employees). As an equal
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of efficient and robust neural networks. About your role: Independent research in the area of mathematics of machine learning, focusing on the development as well as the analysis of different algorithms and
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resources. We offer an international and multi-disciplinary environment with strong expertise in the proposed research fields. The group consists of approximately 17 members at different levels of seniority
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courage to contribute both to the development and application of new methods to investigate the dynamics and consequences of hypoxia in vivo in the context of different pathologies Excellent oral and
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resilience and its change over time in the past (based on Earth observation data), present and future (based on Earth system model simulations for different future scenarios, e.g. using the CMIP6 ensemble and
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Student or Postdoc (f/m/x) in the field of Theory and Methods for Non-equilibrium Theory and Atomistic Simulations of Complex Biomolecules Possible projects are variational free energy methods
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The project will require coding for data analysis and statistics, as well as NGS data analysis. Experience with either of these would be advantageous but an eagerness and commitment to learn is more important