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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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. 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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for different types of multivariate data, such as time series, spatial data, spatio-temporal data, functional data or tensor-valued observations. The work of the postdoctoral researcher will focus on developing
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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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colon cancer (CRC) and its metastasis to distant organs. The goal is to identify microbial strain specific differences in CRC-associated strains using matched oral, normal and tumour samples and their
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hand, forest trees take decades to mature, meaning that the seedlings begin their growth in a different kind of environment compared to the one they face as adults. How will the current forest tree
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participate in a project which investigates and develops novel immunotherapies (cell therapies) to cancer, utilizing both mouse and human systems. Applicants should possess a PhD degree or be close to
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manipulation of developing mouse organs. The project will focus on how signaling pathways operate at the intersection of growth control and branching morphogenesis in the developing mammary gland and will use
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to its employees, including occupational health care and health insurance, unemployment and pension fund, a generous holiday package, sports facilities, and opportunities for professional development
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(FIMM) , University of Helsinki, is currently seeking a highly-motivated postdoctoral researcher to join our interdisciplinary team. Project overview This project aims to develop machine learning models