149 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"University-of-Reading" positions in Sweden
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Do you want to contribute to top quality medical research? Karolinska Institutet (KI) is recruiting researchers as part of the Data-Driven Life Sciences (DDLS) Fellows program. The successful
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information about us, please visit: The Department of Environmental Science . SciLifeLab houses national research infrastructures and has a mission to provide cutting-edge and enabling molecular technologies
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techniques such as SEM, TEM, XRD, EDS, EBSD, FIB/SEM etc., as well as physico-mechanical characterization techniques such as tensile, compression, DSC/TGA, etc. as well as analysis of the data with good
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comfortable generating primary data using advanced molecular, techniques. Experience with mass spectrometry–based methods, spatial metabolomics and/or proteomics, or related technologies is highly desirable
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includes processing satellite time-series data and applying advanced time-series methods for early estimation of seasonal growth curves. Vegetation parameters, such as Leaf Area Index (LAI), will be
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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We are seeking a highly motivated candidate who has recently completed, or is close to completing, a PhD and has training in statistics, data processing, bioinformatics, or a related discipline, to
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, the establishment and optimization of behavioral assays under controlled oxygen conditions, image‑based analyses, and quantitative data processing and interpretation. The role also includes active participation in
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understand them, including multi-omics data, postmortem histopathology, and assembly of massive tau-PET imaging datasets. The Project Assistant will aid these pursuits through processing and analyzing large
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep