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of transcription by RNA polymerase II (Pol II) in normal and disease states. We are particularly interested in essential and biomedical-ly important transcriptional cyclin-dependent kinases (tCDKs) that trigger
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, the Digital Precision Cancer Medicine Flagship (iCAN), and among others. Your mission To qualify, applicants must hold a PhD in computational biology and possess extensive knowledge of biomedical sciences. A
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investigation and will develop an advanced computer modeling framework. By simulating processes at various scales, from the atomistic to continuum, we aim to reveal how temperature and saturation fluctuations
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information about the position may be obtained from Professor Suvi Keskinen, suvi.keskinen@helsinki.fi . Further information about the recruitment process can be obtained from HR Specialist Minna Toivonen hr
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. The position will be filled as soon as possible, or as agreed with the selected candidate. Selection process and employee benefits University of Helsinki welcomes applicants of any gender, linguistic and
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researchers (for further information, please see: https://blogs.helsinki.fi/viikki-postdoc/ ). Application and selection procedure To apply, please send the following documents in a single pdf file: * A letter
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processes contributing to cancer. The candidate We seek a motivated candidate with a strong interest in computational cancer research, who is enthusiastic about applying deep learning methods to cancer data
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regulatory processes contributing to cancer. The candidate We seek a highly motivated candidate with a track record of statistical models, network science, and/or computational tool development dedicated
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offered a fully funded contract of up to 3 years. About the position The postdoctoral research position will require developing and applying cutting-edge machine learning methods to computer vision and
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from buildings, mobile network data) Database management skills (e.g., PostgreSQL) Statistical expertise related to big data processing and high-performance computing (Python, R) GIS software proficiency