PhD in Bioinformatics and Machine Learning for Infection and Antimicrobial Resistance Diagnostics

About this job

About the position The Department of Biotechnology at the Faculty of Applied Ecology, Agricultural Sciences, and Biotechnology (ALB) at the University of Inland Norway (INN) invites applications from exceptional candidates for a PhD position. The position will last for three years. The successful candidate will be based at the Department of Biotechnology. The candidate will be enrolled in INN’s PhD program in applied ecology and biotechnology, and the candidate must work from the designated workplace in Hamar. The appointed PhD candidate will work in the group of Professor Rafi Ahmad. The Ahmad group is also part of the Norwegian Network for One Health Resistome Surveillance (NORSE), a national network of 13 Norwegian institutions. The group is also part of Microbiology Matters (MiMa), a PhD school with work-life relevance that focuses on One Health and infectious diseases. The group is also affiliated with the National Center of Expertise, Heidner Biocluster. The appointed candidate will be working within a proliferating scientific environment comprising academic staff members, Ph.D. students, and research fellows with scientific expertise ranging from theoretical methods (machine learning, biostatistics, and bioinformatics) to experimental methods (genomics, molecular biology, clinical microbiology, microscopy, and spectroscopy). About the project The selected candidate will join the BioAI project, funded by Hedmark Fylkeskraft, which aims to establish a Biotechnology Innovation Centre in Innlandet focused on cutting-edge research in biotechnology and AI. The PhD project will address bacterial infections caused by antimicrobial resistance (AMR), a major global threat to healthcare and society. With few new antibiotic classes developed in recent decades and widespread inappropriate use of existing drugs, treatment options are becoming increasingly limited. At the same time, antibiotics are often prescribed without identifying the causative pathogen or its resistance profile. The selected candidate will also collaborate with and contribute to the the UTI-Diag and OH-AMR-Diag projects funded by the Research Council of Norway. Please find the project details here: https://www.inn.no/english/research/research-projects/UTI-Diag/ https://www.inn.no/english/research/research-projects/OH-AMR-Diag/ The main objective of these projects is to develop a proof-of-concept decision-making diagnostic system for rapid, accurate, and sensitive on-site detection of infections, pathogen identification, characterization of resistance profiles, and prediction of antibiotic susceptibility. Main responsibilities Maintain and further develop a pipeline for pathogen identification from next-generation sequencing data, including ONT sequencing data. Design and implement a new version of the group's pathogen detection software, Voyager. Contribute to algorithm development for sequence analysis and related computational problems Collaborate closely with laboratory-based researchers and clinical partners, translating between computational and experimental perspectives Take on additional computational research tasks as they arise within the group's broader research program Complete a PhD thesis and associated coursework within the 3-year fellowship period Please refer to our latest publications, which highlight our work. • https://www.nature.com/articles/s-66865-8 • https://link.springer.com/article/10.1186/s-06266-2 • https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2023.1154620/full • https://www.biorxiv.org/content/10.1101/2024.04.13.589333v1 • https://www.biorxiv.org/content/10.1101/2025.10.08.681127v1 • https://www.tandfonline.com/doi/abs/10.1080/.2026.2625382 Qualifications It is a requirement that the PhD research fellow qualifies for admission to the University's PhD program in Applied Ecology and Biotechnology. Applicants who already hold a PhD will not be considered. Applicants who have submitted their master's thesis for evaluation before the deadline are eligible to apply, but final documentation must be obtained before an offer of employment is made. To be admitted to the doctoral program, the applicant must normally have a minimum of a master's degree or master's-level education (120 credits, §3 master's in the Norwegian system) in bioinformatics, computational biology, machine learning, computer science, or a closely related field. Furthermore, you must have a strong academic background from your previous studies, i.e., an average grade of B or better in the master's program (120 credits) or equivalent education. The average grade is calculated based on the credits for each course and the master's thesis. Applicants with weaker grades than those normally required for admission must demonstrate that they can complete a doctoral degree. In cases where the education has been approved based on the grades passed/failed, the applicant is admitted after an individual assessment. If you have education from

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