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data (HRMS) used for non-target analysis. The projects aims to develop a combination of supervised and unsupervise machine learning stragaties for pinpointing chemicals that have high toxicity
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applications, including development and validation of machine-learning and statistical models for disease prediction, prognosis, and therapeutic response. Proficient in R, SAS, and other bioinformatic tools
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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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practical skills in the field of data science, especially. multimodal data analysis. Experience on image processing (especially on MRI data) via machine learning. Programming skills (e.g., Python
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vision. Understanding or willingness to learn advanced statistical modeling is a plus Assessment criteria and other qualifications: This is a career development position primarily focused on research
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are looking for a postdoctoral researcher with a strong background in speech synthesis and machine learning, with an interest in accessibility and human communication. Your Role You will: Plan and lead
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Computing Science at Umeå University is looking for a doctoral student in machine learning
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of the SciLifeLab Integrated structural biology platform https://www.scilifelab.se/units/structural-proteomics/ The unit provides access to cutting-edge equipment and expertise, for the analysis
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established in the areas of electronic and electromagnetic simulation and design, machine learning and artificial intelligence in electrical engineering, electrical low-frequency and high-frequency measurement