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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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research across various areas, managed under the Department of Immunotechnology. Through the collaborative project L2Bridge, which is supported during five years by a donation (https://www.lu.se/artikel
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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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) to help shape and accelerate the adoption of advanced machine learning and AI in data-driven Life Science research. At the SciLifeLab Bioinformatics Platform (NBIS), a unique national infrastructure with
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Tryggers Stiftelse and the terms of the scholarship are regulated by the foundation (https://www.carltryggersstiftelse.se/this-is-the-carl-trygger-foundation/). The scholarship is for full-time postdoctoral
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modeling of protein dynamics We are seeking a highly motivated PhD student to join a DDLS-funded project at the interface of structural proteomics, protein biophysics, and machine learning. The position is
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study design, conduct high-quality omics analyses and statistical and machine-learning based modeling, as well as gaining a deeper understanding in extracellular vesicle biology. Work duties and
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is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university