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within this project include: Extending DeepRVAT towards non-coding genetic variation Applying DeepRVAT to population-scale single-cell readouts Integrating population data with experimental perturbation
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support systems. The aim is to develop solutions for key social challenges in areas such as sustainable energy supply, personalised medicine, and networked mobility. Within the MODAL campus, the MedLab
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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. To this avail you will: Define an information model for contingencies, for example, based on ENTSO-E's network code profiles Design a suitable software architecture Research, implement, optimize and document
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for carrying out scientific work Access to national and international networks for your scientific career Family-friendly working conditions that promote the compatibility of work and family life Company-owned
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Innovation Reference code: 50141616_2 ? 2025/KS 3 Commencement date: as soon as possible Work location: Geesthacht Application deadline: June 18th, 2025 The applicant will work in the frame of the EU Research
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artificial intelligence methods. PhD Position – Hydrogen corrosion assessment combining experimental and AI approaches Reference code: 50141225_2 – 2025/MO 2 Commencement date: as soon as possible Work
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, computational model development, data processing, and code implementation in close cooperation with scientists. The position is limited to 3 years. Equal opportunity is an important part of our personnel policy
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independent research with a focus on transnational terrorist actors and networks, their formation and organization, and on policies to prevent, to counter and to cope with terrorist activities; Publication work
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Future. Discover. Together. The Wireless Communications and Networks department of the Fraunhofer Heinrich Hertz Institute participates in the development of new technologies for the next generation