Researcher in machine learning/mathematics applied to cell/developmental biology

Job description

Applicants are invited for a 2 year position as researcher in machine learning/mathematics to be based in the group Cell Stress and Cancer https://www.med.uio.no/imb/english/research/groups/cellstress/index.html headed by Associate Professor Helene Knævelsrud at the Section of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine,

This position is part of the project entitled Final act of the autophagy symphony: whole-organism orchestration of autophagy termination (FINALphagy) funded by the European Research Council. https://www.med.uio.no/imb/english/research/projects/finalphagy/index.html

The researcher will be part of a team aiming to understand how autophagy termination is orchestrated between different organs and tissues in a multicellular organism. This involves using machine learning and mathematical modeling based on data of autophagy responses collected primarily by microscopy, but also other high-throughput techniques. The candidate will use the existing datasets to develop ML methods to predict the properties of autophagy in a whole organism (Drosophila melanogaster). The researcher will also use data and measurements extracted from image analysis and relevant publicly available data sets for mathematical modeling of autophagy termination.

More about the position

The position is for 2 years and devoted to carrying out part of the project FINALphagy. The researcher will work together with graduate students and postdoctoral research fellows on the overall goals of the project.

Qualification requirements

• Applicants must hold a degree equivalent to a Norwegian doctoral degree in mathematics, biostatistics, computer science, computational biology or similar. Doctoral dissertation must be submitted for evaluation by the closing date. Appointment is dependent on the public defence of the doctoral thesis being approved.
• Fluent oral and written communication skills in English.
• Documented coding skills are essential. Experience with machine-learning based analysis of biological or medical images is a strong positive benefit. In addition, experience with mathematical modeling will count positively.

Personal skills

• Scientifically curios and proactive, with drive and commitment to work at the frontier of basic science
• Ability to work independently as well as a part of a team
• Good presentation skills 
• High working capacity and productivity
• Motivated and solution-oriented
• Flexible and effective

We offer

• Salary NOK 575 400 – 657 300 per annum depending on qualifications in position as Researcher (position code 1109)
• A professionally stimulating working environment
• Attractive welfare benefits and a generous pension agreement, in addition to Oslo’s family-friendly environment with its rich opportunities for culture and outdoor activities

How to apply

The application must include

• Cover letter (statement of motivation, summarizing scientific work and research interest)
• CV (summarizing education, positions, pedagogical experience, administrative experience and other qualifying activity)
• Copies of educational certificates (academic transcripts only)
• A complete list of publications
• List of reference persons: 2-3 references (name, relation to candidate, e-mail and phone number)
• Optional: A link to a repository of recent or current work demonstrating experience with coding within the field of machine learning, mathematical modeling or other relevant applications (preferably github)

The application with attachments must be delivered in our electronic recruiting system. Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English (or a Scandinavian language).

In assessing the applications, special emphasis will be placed on the documented, academic qualifications, as well as the candidates motivation and personal suitability. Interviews with the best qualified candidates will be arranged.

Formal regulations

According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

Contact information

Associate professor Helene Knævelsrud, phone 41427591, e-mail: helene.knavelsrud@medisin.uio.no