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collaborators in computational biology, machine learning, and imaging-based profiling. The position involves leading independent research projects at the interface of machine learning and biology, with a strong
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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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of expertise. The group also collaborates with other divisions at Linköping University; mainly the computer vision laboratory at the department of electrical engineering (focusing on deep learning for computer
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and overcoming challenges. Curious, eager to learn, and willing to develop new skills. Collaborative and open‑minded. Other information The position is a fixed-term employment under SÄVA for 12 months
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multiomics across diverse biological systems, including animal and plant tissues. The position offers the opportunity to contribute to method development and experimental workflows in a collaborative and
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of very different backgrounds Ability to collaborate and work in a service-oriented organization. Willingness to learn new methods and the ability to develop new skills. Ability to manage projects
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academic and industrial collaborators. The position is funded by the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) program and the student will integrate into the DDLS
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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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
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approximately 60 doctoral students. The department offers a strong research environment with unique opportunities for synergy and collaboration between theoretical and experimental activities. Access to BSL2 and