12 parallel-processing-bioinformatics Postdoctoral positions at UNIVERSITY OF HELSINKI
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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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. The selection process will involve an initial shortlisting, followed by interviews with selected candidates. The interview may include a small bioinformatics task to be solved by the candidate during
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“Targeting metabolic adaptation to combat difficult-to-treat urinary tract infections caused by E. coli biofilms” led by prof. Päivi Tammela, at the Division of Pharmaceutical Biosciences. The aim
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a probationary period. The appointment is in the Research Council of Finland research project “Targeting metabolic adaptation to combat difficult-to-treat urinary tract infections caused by E. coli
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interest and background in computational biology/bioinformatics are strongly encouraged to consider this opportunity. Our research is funded by the Research Council of Finland, Sigrid Jusélius Foundation
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omics data from human patient samples. Individuals with a strong interest and background in computational biology/bioinformatics are strongly encouraged to consider this opportunity. Our research is
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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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. 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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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