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, implementation of methods in computer codes, use of state-of-the-art high-performance computers in Sweden and in Europe, application of machine-learning and AI techniques, and collaborations with experimental
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application! We are now looking for a PhD in Environmental Science with focus degradation of organic pollutants in biogas processes. Your work assignments The position for a doctoral student is announced as
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are looking for a Data Science application expert The position As the data science expert, you will be responsible for developing techniques to process large-scale data, with a particular focus on managing
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-omics data processing, including integration and analysis of complex biological datasets. • Excellent communication skills in English, both spoken and written, suitable for academic and collaborative
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application! We are looking for up to 10 teaching assistants to the Department of Computer and Information Science. The position We are looking for up to 10 teaching assistants to support examinators in
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bioinformatic pipelines. The analyses will be carried out on GPUs and part will consist of data processing and visualization in order to facilitate interpretation and, in some instances, clinical reporting
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representatives Information about union representatives, see Help for applicants . Application procedure Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University
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departmental duties, up to a maximum of 20% of full-time. Your qualifications We are searching for someone with a Master’s degree in computer science, media technology, computer engineering, human-computer/robot
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application! A brighter future! How does lighting design affect future design and product development processes and how digital tools such as VR/MR can contribute to experimentation and evaluation. Your work
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application! Your work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning