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the state of soils and waters. The department is responsible for several important research infrastructures in the form of soil chemistry and soil physics laboratories, a computer tomography, a lysimeter
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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, which is crucial for rutting, using machine learning. Second, we will develop new systems to integrate data from radar and lidar sensors mounted on drones and forestry machines to improve future real-time
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bioinformatics, with a particular emphasis on performing analysis of high-dimensional data, which can be sequencing and/or imaging-based. Experience working with AI and machine learning approaches are considered a
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includes participating in research projects and third cycle courses. The work duties will also include teaching and other departmental duties (no more than 20%). Your research focus will be machine learning
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or more of the following programming languages/environments: Unity/Unreal, C/C++, C#, Python Basic understanding of the artificial intelligence and machine learning fields. Place of employment: Karlskrona
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commitment to lifelong learning. The department emphasizes strong collaboration between academia, industry, and society, with a clear focus on utilisation. M2 is characterised by an international environment
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Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may
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.) experience with statistical methods (Bayesian statistics, machine learning etc.) We offer Lund University is a public authority which means that employees get particular benefits, generous annual leave and an
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computational biology with a focus on developing new and scalable computational models (e.g. deep learning, machine learning, optimization or statistics) or integrating data-driven applications to address