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Field
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developing and using dedicated tools and processors Contribute to our sparse auto-differentiation libraries to accelerate the training of state-space models Collaborate closely with our internal partners
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systems using various tools and models, including: i) characterization of the emerging patterns in physical systems (solid state materials and active systems); ii) investigation of the mechanical properties
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working atmosphere flexible and family-friendly working time model and the possibility of mobile working (up to 50% of working time) subsidy for a company ticket for public transport
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the diversity of aspartic proteases from the model plant Arabidopsis thaliana and deploy chemical synthesis, advanced modelling, protease biochemistry, mass spectrometry and structural analysis methods. A
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these determinants, we will harness the diversity of aspartic proteases from the model plant Arabidopsis thaliana and deploy chemical synthesis, advanced modelling, protease biochemistry, mass spectrometry and
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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-specific inflammation” and aims to develop and apply advanced imaging tools to study immune cell dynamics in murine models of inflammation and cancer. More about our work: https://www.medizin.uni-muenster.de
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working atmosphere flexible and family-friendly working time model and the possibility of mobile working (up to 50% of working time) subsidy for a company ticket for public transport
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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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the perspective of energy infrastructure. Using the existing energy system models of ICE-2, you will develop scenarios to analyze the effects on the German energy system and its robust design in a European context