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the Kilpinen group (iPSC models of NDDs, scRNA-seq, CellPainting of in vitro neurons, multimodal data analysis) and the Kim group (single-cell multiomics, gene regulatory network modelling, smfISH, in vivo
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at the Faculty of Medicine, University of Helsinki. The project will focus on using and extending deep learning-based approaches developed within the group to integrate bulk multi-omics cancer data. The Kuijjer
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researcher is expected to contribute to research on challenging racism and structural inequalities, antiracism, and everyday struggles of migrants and racialised minorities. The position is based at The Centre
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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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the activity of specific transcription factors using cell biological and sequencing-based (RNA-seq, ChIP-seq, CUT&RUN, PROseq) techniques. Qualifications We invite applications from candidates with a strong
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based on level 5 of the job requirement scheme for teaching and research staff in the salary system of Finnish universities. In addition, the appointee will be paid a salary component based on personal
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to: Develop and apply machine learning models for analyzing complex datasets related to nature conservation. Establish and maintain code and data repositories to ensure efficient workflow and collaboration
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research environment with excellent opportunities to build up your professional expertise and scientific network. The salary of the successful candidate will be based on level 5 of the demands level chart
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trigger, calibration and jet physics expertise in Finland, providing a solid base and collaborators for this project. In addition, the selected candidates have the opportunity to contribute to other
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(e.g., ArcGIS, QGIS) is an advantage What we offer The salary is based on the Finnish university salary system for teaching and research staff, at requirement level 5, with an additional performance