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relationships should then be extrapolated to different ecosystems in European seas, also in support of management efforts. Our team is internationally renowned in the field of trait-based marine modeling. Within
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, with strong ties to Berlin’s broader biomedical landscape. MDC offers structured postdoctoral training programs, access to cutting-edge technology platforms, and opportunities for interdisciplinary
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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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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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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link various actors within the complex area of climate change. The successful candidate will be working in different case study in Europe under the frame of the EU Project NBS4Droughts. The primary goal
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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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) 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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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro