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with a focus on transnational terrorism or related topics in international academic journals and with well-established publishers; Development of grant applications and implementation of research
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marine realms. For this, a suite of thematic VREs will be developed that allow an easy-to-use application of models on available and harmonized biodiversity and environmental data. Both projects provide
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 3 months ago
links between family and health, [2] the role of genetic factors in shaping health inequalities, [3] international comparisons of health and health inequalities, and [4] developing new methods, in
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collaboration and cooperation - intra-institute, national and international, interdisciplinary opportunities to develop – on the job and towards other positions an international environment – everyday contact
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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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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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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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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