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

About the positionThe 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 projectThe 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 responsibilitiesMaintain 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/s41467-025-66865-8   •    https://link.springer.com/article/10.1186/s12859-025-06266-2   •    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/10.1080/14787210.2026.2625382    QualificationsIt 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 abroad, you can contact NOKUT for approval of your education; alternatively, a similar assessment will be conducted as part of the application process.   Required qualifications The required qualifications are: Strong hands-on programming experience in one or more of: C++, Rust, and Java. Strong command-line/bash proficiency and general scripting skills. Previously demonstrated ability to work with algorithmically demanding problems. Experience with bioinformatics pipelines, sequencing data (particularly long-read/ONT), or genomics more broadly. Desired Qualifications Experience with machine learning / AI methods. Experience with infection biology and/or AMR. Experience working in interdisciplinary teams that include experimental/laboratory scientists.   The candidate must also demonstrate proficiency in spoken and written English. Applicants from non-English-speaking countries must document English competence through an approved test (TOEFL, IELTS, Cambridge Certificate in Advanced English (CAE), or Cambridge Certificate of Proficiency in English (CPE). Additional consideration will be given to those with strong teamwork and communication skills and to those with documented scientific publications.   Evaluation of candidates for the position will be based on a comprehensive assessment of educational background, experience, personal suitability, motivation, and other eligibility requirements, as defined in the advertisement. In addition, the following will be emphasized: quality of the project description, documented independent research and development work, or experience relevant to the project. The position and associated tasks must be carried out in accordance with the applicable laws and regulations for government employees, including also the Act on Control of the Export of Strategic Goods, Services and Technology, etc. Candidates who, after assessment of the application and attachments, come into conflict with the criteria in the latter act, will not be able to take up the position at University of Inland Norway. Necessary approvals must be maintained throughout the employment relationship. How to applyThe application and attachments must be submitted electronically and include the following: Application cover letter summarizing the candidate’s motivation and how they meet the position requirements. CV (summary of education and work experience). Copies of academic certificates/transcripts. Minimum of two references with complete contact information. A complete list of scientific and other publications. Attachments must be uploaded as separate files. If the attachments exceed 30 MB, they must be compressed prior to upload. It is the applicant's responsibility to ensure that all attachments are uploaded. Documents submitted after expiry of the deadline will not be considered in the evaluation of your application. If you are awaiting final master's documentation, please submit your thesis and transcript. We offerCollaborating within a multidisciplinary team comprising microbiologists, ML/AI specialists, bioinformaticians, medical professionals, and physicists. Access to cutting-edge computational infrastructure. Involvement in a stimulating and impactful project that contributes positively to society, offering opportunities for both personal and scientific growth. An intellectually stimulating work environment with dynamic colleagues focused on a critical and rapidly growing research field. A flexible and independent work setting where candidates have significant autonomy. Daily interaction with talented and motivated colleagues. Position is paid and placed in position code 1017, PhD candidate in the Government Salary Scale (A paygrade of LT 54). Life insurance and occupational injury insurance are included. Pension contributions to Statens pensjonskasse (State Pension Fund) will be automatically deducted. All residents in Norway are automatically included in the Norwegian public health system. For more information about INN University as an employer, please see here. Video: https://www.youtube.com/watch?v=F0FVnszhpJYGeneral informationFor further details about the position, please contact professor Rafi Ahmad, rafi.ahmad@inn.no, +4762517845 INN believes that there is strength in inclusion and diversity. We desire employees with different competencies, professional combinations, life experiences and perspectives to contribute to an even better way of solving problems. We will facilitate for employees who need assitance to realise their goals. Relevant adaptations can be, for example, technical aids, adapting furniture or adjusting routines, work tasks and working hours. If there are qualified applicants with disabilities, gaps in the CV or immigrant background, we shall call at least one applicant in each of these categories for an interview. In order to be considered as an applicant in these groups, the applicants must meet certain requirements. You can read more on this here: https://arbeidsgiver.difi.no/positivsaerbehandling. We encourage applicants to tick in Jobbnorge if they have a disability, a gap in their CV or immigrant background. The ticks in the jobseeker portal form the basis for anonymised statistics that all state-owned enterprises report in their annual reports Information about applicants may be made public even if the applicant has asked not to be named on the list of persons who have applied. The applicant must be notified if the request to be omitted is not met.