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and childhood, using mobile phone technology (mHealth) to measure diet and physical activity, and to deliver interventions promoting healthier lifestyles. The group also has a strong educational
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-throughput drug screening and single-cell sequencing. The position will be co-supervised by Professor Jens Lagergren at the Division of Computational Science and Technology, Royal Institute of Technology and
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single cell biology technologies as well as antibody engineering, high dimensional flow cytometry and functional assays to understand molecular mechanisms of various autoimmune diseases. The candidate will
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Bionanomaterial Technology Laboratory and research group of Principal Investigator Assoc. Professor Dr. Georgios A. Sotiriou as PhD student in “Nanoparticle-enabled approaches to heal chronic wounds” financed by a
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, technology, social sciences, etc. and is responsible for the master’s program Work and Health. The unit employs several doctoral students and post-docs. The doctoral student will be offered regular seminars
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Science and Engineering, or a closely related field such as signal processing, machine learning, statistics, or bioinformatics. Expertise in image analysis and deep learning models, with a focus on object
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developed a unique automated robotic lab for high-capacity full-length scRNA-seq that can provide state-of-the-art splicing information across complex tissues. Using this scalable scRNA-seq technology, we
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medium holding a lot of promise is DNA as, if the technology gets fully realized, it offers several advantages: high storage density, exceptional stability on long timescales among other things. However
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Computer Science and Engineering, or a closely related field such as signal processing, machine learning, statistics, or bioinformatics. Expertise in image analysis and deep learning models, with a focus on
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engineering, all working together to improve atherosclerotic and vascular disease diagnostics. Leveraging unique cohorts and biobank data, the student will also be directly involved in cutting-edge data-driven