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School of Electrical Engineering and Computer Science at KTH Project description Third-cycle subject: Electrical Engineering The department of Decision and Control Systems (DCS) is currently seeking
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, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and analytical understanding; Proficiency in programming in Python
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experience in areas such as advanced image analysis, data structuring and data integration, and large language models (LLMs) with applications in biological and biomedical research. The successful candidate´s
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of reproducible code through code sharing platforms, version control, workflow languages and container solutions. Documented ability of responsible and legally compliant adoption of machine learning/AI methods
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on community ecology. Researchers have access to excellent glasshouse and climate-controlled facilities, fully state-of-the-art molecular labs and a high-performance computing cluster (UPPMAX). The Department
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model organisms, their application in conifers remains limited due to challenges associated with tissue structure, nuclei isolation and sensitivity to inhibitory compounds. This project aims to develop
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workflows. •Operation and monitoring of LC-MS/MS and LC-HRMS instrumentation. •Routine quality control and assessment of analytical performance. •Documentation of laboratory work and analytical results
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and further develop its research and education in this area. The department has purpose-built infrastructure for advanced metabolic studies in mouse and rat models. The successful candidate is expected
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of reproducible code by using code sharing platforms, version control, workflow languages and container solutions is a merit. Experience in training deep learning-based models on HPC-resources is also meriting. A
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics