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your application. Reference letters may be requested via an electronic submission process as your candidacy is considered. The position is currently limited to 2 years and may be renewed for one more
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will focus on the prediction of genetic interaction networks and image analysis for automated phenotyping. We welcome interest in developing both ongoing and novel research projects in the lab, and are
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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data and clinical information. Applicants must hold (or be close to completing) a PhD in a relevant field and have expertise in modern computer vision and AI research. Experience with biomedical data
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collaborative mindset and bring the following qualifications: a PhD degree in mathematics, with a focus on algebraic geometry; experience with at least some of the following: Fourier—Mukai transforms, Hochschild
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normal and pathological feeding and reward processes. Applicant must hold a PhD or equivalent degree in neuroscience, biochemistry, molecular biology, psychology, computer science, biomedical engineering
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); units such as onboard computers, mass memories, remote terminals and instrument control units*; digital and analogue signal processing electronics for payload/platform functions; front-end acquisition and
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, imaging techniques, and bioinformatic analysis. Successful applicants will need to work both independently and collaboratively, to exhibit excellent skills in scientific communication, and dedicated
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: Ph.D. in Electrical Engineering, Applied Mathematics, Biomedical Engineering, Mechanical Engineering or related fields. Preferred Experience: Experience in MRI and post-imaging processing Preferred Field
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the project. Qualified candidates should have: A PhD degree in Computer Science, Electrical Engineering or equivalent. Research interests and a scientific track record in Edge Computing research fields, such as