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professional development opportunities and strive to meet each individual’s development and well-being goals as much as possible. As an associate researcher with expertise in the field of machine learning within
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Mathematics,' and 'Computer Vision and Machine Learning' at the Faculty of Engineering, as well as Mathematical Statistics, which is cross-faculty. The position is located at the Division of Mathematical
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sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models that unlock
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involve collaborating with our researchers to process occupational classifications, harmonize census data, develop machine learning models, run statistical models, and write research articles
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existing omics and machine learning-based pipelines to process and postprocess this data. The Project Assistant will be encouraged and given the opportunity to lead their own project analyzing proteomics
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to measure these backgrounds in data. The project also aims to explore to which extent machine learning methods can help with these tasks, e.g. object reconstruction and signal vs background discrimination
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applying deep learning and/or machine learning models to medical imaging data. Other information This is a permanent position, 100 % of full time. Starting date in October 2025 or according to agreement. How
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chemical and mineralogical analyses (e.g., XRD, SEM, geochemistry). AI and machine learning applications: Develop and apply AI methods to identify patterns and relationships between geophysical parameters
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of research? Find more reasons why Lund University and the HT Faculties is right for you here , and learn more about Working in Lund , Moving to Lund and Living in Lund . QualificationsQualification
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population registries and biobanks. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning