106 computer-science-intern "https:" "https:" "https:" "https:" uni jobs at Nature Careers in Germany
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implementation of a website project and coordinate internal teams, external service providers, and stakeholders to ensure smooth implementation. You will develop strategies and action plans to achieve the project
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microdissection Basic immunofluorescence staining Your profile Enrolled in a Bachelor's or Master's program in Biology, Biochemistry, Biomedical Sciences, or a related field Prior lab experience in tissue handling
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of radioactive materials Further development of the state of scientific safety assessment at national and international level Initiation of engineering research and development work for the experimental and
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PhD in computer science, physics, mathematics, or a related discipline Strong expertise in image analysis and/or machine learning, with a deep understanding of how data characteristics impact downstream
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confidently differentiate by channel, format, and audience, and skillfully adapt your style for specialist audiences, media representatives, and the general public. You write national and international press
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Cryosectioning and laser capture microdissection Basic immunofluorescence staining Your profile Enrolled in a Bachelor's or Master's program in Biology, Biochemistry, Biomedical Sciences, or a related field Prior
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the MPG. You will lead a high-performing team in a world-class international environment, supported by in-house engineering, high-performance computing, and the services provided by the Max Planck Society
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collaboration partners Your Profile Academic degree (M.Sc. and Ph.D.) with a background in computer science, bioinformatics, physics, or a related field Proven experience in next-generation sequencing (NGS) data
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research by developing and combining enabling technologies. Our major research fields are AI-based organ mapping, Tissue engineering and Precision medicine in cancer treatments. Sophisticated technologies
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state-of-the-art computational and high-throughput experimental validation methods in functional, de novo protein design. Over the next two years, the team will jointly develop computational methods