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at undergraduate and master’s levels, primarily in data science, machine learning, and AI programming in Python, including lecturing, supervision of student projects, course development and examination. Scholarly
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of Medical Sciences can be found at https://www.uu.se/en/department/medical-sciences . The Affinity Proteomics unit at SciLifeLab, hosted at Uppsala University, is seeking a highly motivated biofinformatician
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scheduling systems. Basic programming skills in Python are required, as well as experience working with biological or biomedical datasets. The successful applicant should demonstrate the ability to work both
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(see below) are also encouraged to apply. Proficient in at least one programming language, preferably Python or R. Experience in any of the following areas: large scale sequence analysis, microbial
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, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS
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of experience in training, evaluating, and deploying machine learning models, including deep neural networks and relevant frameworks - Documented several years of experience in systems development with Python and
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identification, optimization, or numerical methods is valuable, as is knowledge of data analysis and machine learning for complex, high-dimensional systems. Programming experience in MATLAB or Python, and an
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, neuroscience, electrical engineering, or a related field, hands-on experience with neural recording and/or stimulation techniques, signal processing, and data analysis (e.g., MATLAB or Python), experience
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, Applied Physics, Nanotechnology, or equivalent. Strong programming skills in high-level languages, specifically Python. Good verbal and written communication skills in English. A collaborative attitude and
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experience (preferably in Python or MATLAB) We offer Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension