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disposal strategies and sustainable resource management practices. The project also has synergy the ongoing EURATOM EURAD2 RAMPEC work package, and it is expected that some of the methods developed in HiFi
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advancement of modern artificial intelligence (AI) methods in drug discovery and development. An ideal candidate will have strong background in machine learning, computational chemistry, or related fields, with
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use a variety of molecular and cell biological methods together with bioinformatic approaches to evaluate the zoonotic potential of newly discovered henipa-like viruses in shrews. As a PhD student, you
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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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support services, e.g. research software engineers. Qualifications An ideal applicant has: A doctoral degree in a suitable field for the work to be carried out. Research experience after completing
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methods to understand the regulatory mechanisms driving cancer heterogeneity and progression by integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal
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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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practices in chemical, rheological, and textural analytical methods. Excellent written and verbal communication skills in English. Strong motivation to conduct high-quality research, publish in peer-reviewed
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doctoral researcher is expected to: Advance the BIOBANG project’s objectives as part of a dynamic interdisciplinary team. Conduct doctoral studies and research leading to a completed PhD thesis within 4
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expected to: Develop and apply quantitative methods specifically tailored to the goals of the BIOBANG project. Establish and maintain code and data repositories to ensure efficient workflow and collaboration