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A postdoctoral research associate position is immediately available in the lab of Dr. Yunlong Zhao. Project Description: Dr. Yunlong Zhao , Assistant Member in the Center of Excellence for Pediatric
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. superlattices) this architecture has unparalleled scope for quantum property design. Your particular focus will be on developing a novel characterisation platform that allows fully functional devices to be
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for pediatric diseases. Project Description: Our research focuses on how genetic variants contribute to diseases during early development and on developing mechanism-driven therapeutics. While animal models have
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interdisciplinary research project on production of proteins for food based on a feedstock of CO2 and energy. The positions are based at AU Viborg and/or at AU main campus and are expected to begin on 1 September
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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
Empirical Software Engineering (EMSE). This position is funded by Innovation Fund Denmark Grand Solutions project “AI4SE1DK – Human-Centered Adoption of Artificial Intelligence for Software Engineering in
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to the social working environment and incorporate stakeholders’ interdisciplinary knowledge. We also expect that you will take part in EU project meetings, activities in relation to our new education, and that
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backgrounds, many of whom are internationally renowned. Post-doctoral Fellowships and Research Assistant Professorships Applications are invited for a number of positions as Post-doctoral Fellow (PDF) and
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productivity, e.g., a first author paper, or a demonstrable contribution to a large project. Experience in immunology or cancer immunotherapy or single-cell technologies is desired. The initial appointment will
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the Department of Epidemiology and Cancer Control at St. Jude Children's Research Hospital. Successful candidates will work on projects related to pharmacogenomics of long-term toxicities of cancer therapy in
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skills and curiosity about complex systems. Position Overview You will design and implement new computational and statistical models to reverse-engineer causal networks from noisy, high-dimensional, multi