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. We will develop an isotope version of a process-based CH4 model and update the representation of different wetland types in the model using a data inversion approach. Additionally, we will analyze
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metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
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medication security are challenged by the high costs of development, manufacture and distribution, evaluation of preclinical safety and efficacy, and the dependence of drug manufacturing on international
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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Sini Laakso’s lab Autoimmune Neurology at the Translational Immunology Research Program at University of Helsinki, Faculty of Medicine invites applications for the position of POSTDOCTORAL
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potential. Our research focuses on Materials physics, Quantum technology, Soft & living matter, and Advanced energy solutions. Topics extend from fundamental research to important applications. We educate
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the candidate can start in autumn 2025. Background Our group develops and applies systems pharmacology strategies to design rational combinatorial therapies for cancer. We combine both computational (dry-lab) and
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responsibility can relate to for example some of the following research topics. You are naturally welcome to suggest your own research plan: Development and use of generative AI for de novo molecular synthesis
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some of the following research topics. You are naturally welcome to suggest your own research plan: Development and use of generative AI for de novo molecular synthesis, enabling the design of novel drug
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transdisciplinary research on ethnic, cultural, linguistic, religious and socio-ecological diversity. The action aims at offering novel insights into diversity that will contribute to the development of multi-level