775 computer-programmer-"https:"-"Prof"-"https:"-"https:"-"https:"-"https:"-"CUBO" positions at Nature Careers
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Presentation of results in a small group seminar Your qualifications: B.Sc. in Science or Engineering Enrolment at a German University Basic knowledge of Linux computing environments, including batch and/or
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Job Summary: Responsible for leading and managing an independent research group within the Generative Biology Institute (“GBI”), delivering a program of bold, ambitious and transformational research
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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leadership with a plan for significant expansion, we seek creative applicants with bold vision and demonstrated excellence in immunology research, including (but not limited to) the following areas: 1
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administrations of Helmholtz Munich and TUM, external partners, and funding institutions worldwide. Plan, organize, and participate in scientific meetings and workshops in Munich and abroad. Review and edit
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job performance and ensure compliance with institutional standards. Employee Assistance Program (EAP): Promote the utilization of the EAP, and support employees and managers through return-to-work
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limited to electrophysiology, imaging, ultrasound, TMS, and computational approaches, are strongly encouraged to apply. The ideal candidate will have a track record of discovery and application of basic
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the molecular to cellular scale. We are looking to appoint an individual who has strengths in both experimental and in advanced computational methods in Cryo-EM. The post-holder will work in collaboration with
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research and study programmes are recognised nationally and internationally. FKF is unique in Denmark, bringing together three strong natural science disciplines in one department. This gives us the
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within databases. Develop web services to query the database. Develop and implement computational and systems biology approaches for network and hidden driver analysis for genomic transcriptomics