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Field
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; for more information, please refer to our website ( www.solvation.de ). WHAT WE OFFER: You will be embedded in a high-profile research environment with access to the latest research infrastructure. You will
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to online interviews in February/March, followed by interviews in Berlin. Successful candidates start their doctorate between May and December 2026. For more information on available projects, eligibility
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doctorate between May and December 2026. For more information on available projects, eligibility criteria and the application process, please check the IMPRS‑IDI website . Contact: IMPRS-IDI Coordination
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sequencing, genome-wide data integration, statistical modeling, and hypothesis-driven experimental design, preparing them for leadership roles at the interface of molecular biology and data science. Your Tasks
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engineering Knowledge of machine learning (deep learning) Basic knowledge of computer science or software development, e.g., using Java, Python, or C++ Good communication and information skills, goal-oriented
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distinct mutations can lead to similar developmental issues. More information can be found on our homepage . Project Summary Core gene expression machineries are highly conserved across species, yet tissue
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relating the experimental data back to clinical datasets. We are an enthusiastic and international team and offer intensive training and mentoring. Your Tasks The successful candidate will have the
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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modelling in various plant species. All available projects are detailed where applicants will also find more information about the host groups. Your profile You are a highly qualified and motivated student
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and RNA-seq techniques (including data analysis) Cellular metabolism Mammalian tissue culture and cell manipulation Fluency in English (knowledge of German is not required) Our Offer: Scientifically