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Field
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Infrastructure? No Offer Description Full time, fixed term for 2 years with the possibility of extension Join the School of Electrical and Computer Engineering and contribute to pioneering research redefining
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portfolios when appointing academic staff at the University of Copenhagen. The recruitment process Further information on the recruitment process at University of Copenhagen can be found here: https
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engineered models. • Small-animal surgery, colonoscopy/endoscopy, or in vivo imaging. • Tumor–immune cell co-culture systems. • qRT-PCR, Western blotting, immunofluorescence, immunohistochemistry, or related
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for immunological tolerance during autoimmunity and transplantation, directed at therapeutic intervention strategies. We are using autoimmune animal models to understand biological processes involved with autoimmune
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following areas is desirable: collection and analysis of dense nodal seismic datasets, ambient noise tomography, high-performance computing, machine learning applications in observational seismology, and
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a single-cell imaging laboratory and integrating single-cell data with population-level data. Duties include: The competitive selection process is open for all individuals, who meet the requirements
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multidisciplinary, NIH-funded research program at the interface of molecular imaging, antibody engineering, cancer biology, drug development, and translational oncology. Our laboratory develops next-generation
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Engineering, Computer Engineering, Mechatronics Engineering, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or other related subjects. Experience working on experimental
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computing, obtained within a maximum of 7 years; application of machine learning and deep learning methods to remote sensing images; proficiency in programming (R, Python, or similar); ability to work
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engineering, substrate recovery strategies, manufacturing process development and process integration. The ultimate goal is to establish scalable and sustainable manufacturing methodologies that reduce material