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funds for scientific travel Opportunity for professional development including co-supervisory experience Flexible working conditions Attractive benefits incl. subsidy for public transport across Germany
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of longitudinal cognitive data. Within this group led by Dr. Luca Kleineidam, the applicant will work on challenging and rewarding projects in a friendly and supportive team. Your tasks: Conduct and development
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interfaces (application programming interface, API) for system control are being developed in order to automate both process monitoring and process control. The API-based integration of the digital twin
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for the compatibility of family and career Support for career development A positive working atmosphere in a supportive team Good access to laboratory resources and to data of the Dortmund Vitalstudy An interesting and
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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team to work on machine learning-supported rapeseed genomics and breeding. Your tasks: You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes. You
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opportunity to be an active part in the establishing of our department Comprehensive training programs and individual opportunities for personal and professional development Access to a strong research network
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Your Job: We are looking for a researcher to develop and apply machine learning models for genomic data in our lab. We focus on sequence analysis, genomics, semantics, and cross-domain data
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project led by the MDC/Helmholtz Imaging, GEOMAR, Hereon and FZJ, fully committed to Open Science. We are looking for a PhD student or Postdoc or Research Software Engineer to join our highly vibrant and
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opportunity to be an active part in the establishing of our department Comprehensive training programs and individual opportunities for personal and professional development Access to a strong research network