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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in
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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
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interdisciplinary research environment More information about Jönköping University as a workplace, conditions and benefits on www.ju.se . Required Qualifications Applicants must have been awarded a PhD in Computer
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evaluated and validated using uniquely integrated historical datasets comprising environmental, social, demographic, mobility, and epidemiological information. The successful candidate will contribute to a
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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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research competence, Contact information for two referees who are willing to act as references, Other documents that the applicant wishes to claim. The application, including attached documents, must be
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working with associated techniques, such as bioprinting, is considered an asset. To be eligible for the position, the applicant must be able to analyze and interpret data, have excellent oral and written
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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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exposures and breast cancer risk. The focus of the project is on analyses of high dimensional and longitudinal data. The position is for three years, starting summer/fall of 2026 or upon agreement
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glial cells into neurons. Your main tasks will include 2D and 3D neural culture work and potentially, tissue preparation, histological and molecular analyses, statistical methods, and data presentation