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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab
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or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide data analysis support to data
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. SciLifeLab Lund is comprised of a consortium of nine advanced research infrastructures, with a broad spectrum of focuses that include genomics, proteomics, imaging, structural biology, pharmacological
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intracellular or extracellular bacteria. Analysis of DNA damage markers, levels of m6A machinery (writers, erasers and readers), and host cell response in 2D and 3D culture models by biochemical and imaging
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Assistant Professor in artificial intelligence (AI) with a focus on precision medicine (PA2025/1776)
based on multimodal data that have the potential to result in a paradigm shift from focus on “prevention with one size fits all” to “precision prevention”, the latter meaning specific preventive therapies
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equality and diversity as a strength and an asset. The Department of Process and Life Science Engineering (PLE) at Lund University is located at Kemicentrum, one of the Nordics' largest centers for education
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foundations in all activities at Chalmers. Application procedure The application should be attached as PDF files, as below: CV (max 1 page) Motivation letter (max 1 page) Please use the button at the bottom
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to assess and ensure the safe, predictable, and transparent behavior of systems incorporating machine learning and generative models. Design and prototype frameworks or tools that support systematic V&V
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questions. • Practical experience with GIS tools ArcGIS or QGIS. • Experience working with GIS-related research data, including data collection and processing. • Ability to develop “ready-to-use” solutions