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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 5 days ago
for Demographic Research, Rostock This network focuses on “scientifically motivated engineering” to design, build, and test digital prototypes—such as machine learning models and large language models—that serve as
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characteristics. Nominate and help evaluate promoter regions and candidate genes to enhance nitrogen use efficiency. Apply machine learning models to classify molecular variants as functional and assess
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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computational datasets of disordered materials based on density functional theory calculations and training machine learning models to accelerate the predictions. This work will involve collaboration with Assoc
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digital health and multi-agentic coordination. This role requires the development of self-learning artificial intelligence models tailored for dynamic healthcare environments. The candidate designs and
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. About the Role The post is funded
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
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complex designs, and conducting big data analyses using advanced statistical models. Experience in the use of various datasets, e.g., TOPMed, UK Biobank, All of Us, and/or digital health data, is also