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communications theory methods Applying optimization techniques and machine learning/AI approaches Conducting simulations and experimental validations Collaborating with Ericsson and Chalmers researchers Publishing
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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. Previous experience with machine learning applications in molecular modelling, including experience with at least three of the following Python libraries: TensorFlow, PyTorch, JAX, RDKit. Previous
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Python) and data analysis or machine learning applied to materials science Ability to work in interdisciplinary project or industrial experience About the employment The employment is a temporary position
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value chains to enable AI-based applications, using methods and models from e.g. operations research, data analytics or artificial intelligence/machine learning. Identify, structure and prioritise
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of extensive datasets. You will be supervised researchers who collectively offer expertise in computational biology, genetics, epidemiology, and machine learning. The research will be closely linked
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student in Statistics who can perform high quality statistical research. Apply January 6, 2026, at the latest. We are seeking a PhD student within the WASP-HS project “Machine learning to study causality
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LTU’s strong established competence networks. Duties As a PhD student, you will perform both experimental and theoretical work. You will learn how to collect and analyze scientific data within your
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communicated to practitioners through LTU’s established competence networks. Duties As a PhD student, you will perform both experimental and theoretical work. You will learn how to collect and analyze scientific
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access to preventive care and neighborhood characteristics influence long-term health trajectories. The project applies both econometric and machine learning approaches to identify high-risk groups and to