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requirements and tenure track appointment criteria. The salary is determined according to the salary system for university teaching and research personnel. The pay will include an individual pay component based
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-PCR, microscopy and computational analysis skills (such as RNAseq, sc-RNseq analysis) are considered advantageous. The applicant should have the ability to work productively both independently and as
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experimentation to develop integrative metamodeling approaches, qualitative systems analysis methods and causal graph-based solutions for machine learning. The team aims to advance innovative and robust solutions
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, possessing expertise in cell signalling, cell and tissue imaging and analysis, with experience in 'omics' technologies and bioinformatics approaches. Essential qualifications High level of motivation, capacity
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of document analysis (including AI-assisted analysis) and research interviews. Additionally, you will familiarize yourself with recent research literature in the field by preparing a literature review on
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computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning
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determined in accordance with the University of Turku’s salary system for teaching and research personnel. The job requirement level for the position is between levels 2 and 4. In addition, a salary component
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or interest in: requirements engineering, software testing, software refactoring, or software quality analysis. Other Skills: Ability to work independently and in international, multidisciplinary teams. WE
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. The salary of the positions will be based on salary system of Finnish universities for teaching and research personnel. In addition, the appointee will be paid a salary component based on personal performance
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contribute to several aspects of the project, including the analysis of EUV observations (both on-disk and off-limb) and in-situ measurements, modeling of coronal magnetic fields to map magnetic connectivity