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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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natural language processing techniques to analyze digital content such as images, videos, and textual content that relate to human-nature relationships, with a focus on data derived from digital platforms
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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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should hold a PhD degree in molecular biology, biochemistry, cancer biology or related fields. Expertise in biochemistry, transcriptomics, NGS data analysis and basic programming in R/Python is a pre
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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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sensitivity of biosensors to improve existing sensors and to enable new technologies for a wide range of biomarkers and application areas. Skills, expertise and/or qualifications Doctoral degree (PhD
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8 Mar 2025 Job Information Organisation/Company UNIVERSITY OF HELSINKI Research Field Biological sciences Medical sciences Chemistry Researcher Profile Recognised Researcher (R2) Established
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. Applicants must have a doctoral degree in geography, geoinformatics, computer science, data science, or a related field. Advanced PhD candidates are also encouraged to apply, however the appointee must have a
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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