45 algorithm-development-"Prof"-"Prof"-"Prof" positions at UNIVERSITY OF HELSINKI in Finland
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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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this project we will develop novel models for estimating the correctness of genome and metagenome assembly and algorithms and data structures for computing such correctness estimates. The Doctoral Researcher is
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related to information technology. As a Research Software Engineer at the University of Helsinki, you will get to collaborate with different research groups providing software development and consultation
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The TrueScreen Research to Business (R2B) project at the University of Helsinki is seeking a talented and highly motivated Bioinformatician / Research Software Engineer or Postdoctoral Researcher
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the research group of Professor Klaus Nordhausen in the project “Signal recovery in noisy spatial data”. The research group develops modern and efficient multivariate statistical methods tailored
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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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. 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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to the development of reproducible analysis workflows and pipelines. You have a PhD in bioinformatics, computational biology, data science, computer science, genetics or other relevant field. You have successfully
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the physiological and pathophysiological implications of cellular metabolism, with possible relevance to human health. Experience in utilizing and developing relevant experimental approaches, such as
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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