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to expanding into new competence areas. The candidates must 1) have a strong interest in integrating genetics, data management and management of biological processes, 2) have demonstrated experience in data
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”. This project research techniques for intelligently automating processes for large-scale simulation of robots and mobile machinery that operate in and physically manipulate dynamic environments. Research
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”. This project research techniques for intelligently automating processes for large-scale simulation of robots and mobile machinery that operate in and physically manipulate dynamic environments. Research
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atmospheres, their origin and how they are expected to evolve in a changing climate. Spectral 2D and 3D numerical solvers based on spherical harmonics will be used for the project to perform simulations aimed
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can show indication of capacity to expanding into new competence areas. The candidates must 1) have a strong interest in integrating genetics, data management and management of biological processes, 2
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to automate the process of species classification. However, there are still several methodologies that need to be developed to integrate these models into a functioning workflow for ecologists. In this 4-year
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adaptation and high-versus low intensity forestry. We use empirical and process based modelling, with input data from the National Forest Inventory and long-term experiments. Qualifications: The applicant
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purposes, addressing issues on climate change adaptation and high-versus low intensity forestry. We use empirical and process based modelling, with input data from the National Forest Inventory and long-term
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at cell membranes to regulate key processes in cellular signaling. By combining computational modeling with experimental data, the project aims to uncover how molecular features shape mesoscale cellular
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penetrated many new application areas. Examples include control of autonomous vehicles based on video data, simulation-based prediction of turbulent flows and precision medicine based on gene sequencing time