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PhD Fellow in Machine Learning for Antimicrobial Resistance
UiT The Arctic University of Norway
UiT is a multi-campus research university in Norway and the northernmost university of the world. Our central location in the High North, our broad and diverse research and study portfolio, and our interdisciplinary qualities make us uniquely suited to meet the challenges of the future. At UiT you can explore global issues from a close-up perspective.
Credibility, academic freedom, closeness, creativity and commitment shall be hallmarks of the relationship between our employees, between our employees and our students and between UiT and our partners.
Faculty of Science and Technology
A PhD position is available at the Department of Physics and Technology with the Machine Learning research group. This is a joint project between the Machine Learning Group and the Research group for Host-Microbe Interactions at UiT in collaboration with the Department of Biostatistics at UiO combining machine learning and bacterial genomics to find determinants/targets involved in the interaction between microbe and human for future intervention. The position is also affiliated with the Centre for New Antibacterial Strategies.
The position is for a period of four years. The nominal length of the PhD program is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete research training to the level of a doctoral degree. Admission to a PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position.
The position's field of research
We are seeking a PhD Fellow to take an active role in the group's research on developing novel machine learning methodology for prediction of targets overrepresented in the genomes of problematic antimicrobial resistant bacteria. Antimicrobial resistance is an increasing challenge for the management of bacterial infections which will have severe medical, societal, and economic consequences. New strategies for future infection control and prophylaxis are urgently needed specifically for certain multidrug resistant pathogens recognized by the World Health Organization. The specific aim of the advertised project is to use machine learning algorithms to identify new microbial targets to prevent and control infections for one such multidrug resistant pathogen, Enterococcus faecium.
We are particularly seeking a candidate that has a machine learning background and is familiar with traditional techniques such as random forests and linear regression (for instance, Lasso and elastic nets) as well as deep learning. The candidate should have experience working in Python and/or R. Additionally a background in Biology is highly beneficial, but not required.
The PhD fellow will be a part of the UiT Machine Learning Group. She/he will interact closely with the collaborators at UiT and UiO and develop new machine learning methodology to identify microbial targets, which can be tested by members of the Research group for Host-Microbe Interactions at UiT.
Further information about the position and UiT is available by contacting:
- Michael Kampffmeyer, phone: +47 90602098, email: [email protected]
The position requires a Master's degree in physics, mathematics, statistics, bioinformatics, computer science, electrical engineering or machine learning. A good background in machine learning, or related fields such as pattern recognition or computational statistics, is in any case required.
We are looking for an interested, active and highly motivated candidate, who likes to explore new technologies, is both independent thinking and also enjoys working in a collaboration with others. Good communication skills in English are necessary and documented fluency in English as stated here is required: Proficiency in English - PhD level studies. Good oral and written command of a Scandinavian language is considered an advantage in connection to teaching duties.
During this assessment process, emphasis will be put on your potential for research as shown by the Master's thesis and any other academic works. In addition, we may consider work experience or other activities of significance for the PhD studies. The assessment will emphasize motivation and personal suitability for the position.
Admission to PhD programme
The position requires admission to the PhD programme. Admission requires that the applicant has at least 5 years of higher education, equivalent to 300 ECTS. The applicant must have a Master’s thesis evaluated equivalent to 30 ECTS or more, or 20 ECTS for an integrated Master’s degree. The applicant must have grade C or better on the Master’s degree, and an average of C or better.
Applicants with a foreign education will be evaluated on whether the educational background is equivalent to Norwegian higher education. We use national guidelines according to NOKUTs country database. Applicants from some countries will have to document additional higher education in order to be admitted.
Your application must include:
- Cover letter explaining your motivation and research interests
- Diplomas, diploma supplements and transcripts (all degrees)
- Documentation on English language proficiency
- Contact information to 1-3 references
- Master thesis
You may also submit academic works which you wish us to consider during the assessment process.
Qualification with a Master’s degree is required before commencement in the position. If you are near completion of your Master’s degree, you may still apply and submit a draft version of the thesis and a statement from your supervisor or institution indicating when the degree will be obtained. You must have completed your degree before commencement in the position.
All documentation have to be in English or a Scandinavian language. Submit applications electronically through Jobbnorge.
Terms of employment
Remuneration of PhD positions are in salary code 1017, and normally start at salary grade 50 on the pay scale for Norwegian state employees. There is a 2% deduction for contribution to the Norwegian Public Service Pension Fund.
You have to be qualified for and participate in our PhD study program. As many as possible should have the opportunity to undertake organized research training. If you already hold a PhD or have equivalent competence, we will not appoint you to this position.
More practical information for working and living in Norway can be found here: Welcome to UiT!
The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information for applicants.
A shorter period of appointment may be decided when the PhD Fellow has already completed parts of their research training programme or when the appointment is based on a previous qualifying position PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years.
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background. UiT will emphasize making the necessary adaptations to the working conditions for employees with reduced functional ability.
We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According to Offentleglova information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure. You will receive advance notification in the event of such publication, if you have requested non-disclosure.