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analysis of complex, longitudinal, and high-dimensional data (e.g., immunometabolic profiles, clinical data, biomarkers). Development and application of predictive models and algorithms for diagnostics
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properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
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apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
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setting. In this environment, our research group focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are
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application! Work assignments Our current research projects focus on distributed radar sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine
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involves a collaboration between the Mijakovic lab and Mölnlycke Health Care (MHC), a world-leading producer and distributer of wound care products. The aim of the project is to functionalize existing
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industrial applications. The division has been actively involved in research projects funded by the EU, Swedish state agencies, and the Swedish power industry, covering topics such as active distribution grids
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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through X-ray imaging study structure/morphology on fibre level, providing quantitative descriptors (dimensions of structural building blocks, size distributions, porosity, etc.) and reveal the influence
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distributed acoustic sensing, aiming to establish a solid physics-based foundation for seismic monitoring using existing telecom infrastructure. Who we are looking for Mandatory qualifications PhD degree in