About the host research group and research theme:
The project will be conducted at the Computational Biology Unit (CBU, https://cbu.w.uib.no/ ), hosted within the Department of Informatics at the University of Bergen. The CBU is a leading bioinformatics research hub in Europe, encompassing 10 research groups from five diverse departments (Informatics, Biological Sciences, Chemistry, Biomedicine, and Clinical Science) in a uniquely interdisciplinary environment.
The project will be supervised primarily by Professor Anagha Madhusudan Joshi-Michoel, who specializes in applying machine learning and data science approaches to understand human health and disease, with a particular focus on women’s health, the project aims to contribute to this field. More about the Joshi group can be found at https://cbu.w.uib.no/joshi-group/. Co-supervisors include experts in machine learning and AI, Pekka Parviainen and Tom Michoel, alongside leading epidemiologists, Tone Bjørge and Kari Klungsøyr.
The core research objective of this project is to integrate machine learning and AI to bridge population level data (epidemiology) and genomics (bioinformatics) to enhance public health outcomes, with a particular focus on women’s health. The long-term goal is to develop innovative diagnostic tools to predict adverse female health outcomes by integrating extensive epidemiological and molecular data from three continents: the United States, Norway, and India. Specifically, the project will integrate diverse epidemiological data (health registry data from Norway, CDC data from the US, and NFHS data from India) with genomics data (transcriptomics, metabolomics, GWAS, protein-interaction) to identify causal relationships and common molecular pathways in women’s health-related diseases and disorders. By developing advanced machine learning methods, the goal is to create a diagnostic and early risk prediction tool that, if successful, could enhance the prevention, diagnosis, and treatment of female morbidity and mortality.
About the LEAD AI fellowship programme
LEAD AI is the University of Bergen’s career and mobility fellowship program for training 19 postdoctoral fellows in artificial intelligence.
The program has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101126560.
The LEAD AI programme offers high-quality inter- and transdisciplinary research and training opportunities in the area of artificial intelligence supported by a dedicated supervision and mentoring, encouraging inter-sectoral exposure, in particular:
• academic freedom
• benefits from knowledge and skills transfer between disciplines, organisations and sectors
• structured, skill-based training
• high-quality working conditions
• personal career support
• equal opportunities
For more information see the LEAD AI webpage or send an email to leadai@uib.no
Qualifications and personal qualities:
- Applicants must hold a Norwegian PhD or an equivalent degree within computer science, computational biology, bioinformatics, Physics, Mathematics, Biology (with strong programming skills), or related field., or must have submitted his/her doctoral thesis for assessment prior to the application deadline. It is a condition of employment that the PhD has been awarded.
- Applicant should have a genuine interest in AI and women’s health, and the research proposal must be related to artificial intelligence and women’s health.
- Applicants cannot previously have been employed as a postdoctoral fellow at UiB and they cannot be employed by any other institution for the time of the fellowship.
- Experience with machine learning techniques is an advantage.
- Experience with the analysis of omics data is an advantage.
- The LEAD AI mobility rules must be followed.
- Outgoing fellowships require an uninterrupted stay of minimum 12 months at an institution outside of Norway, followed by a mandatory return period to the University of Bergen of at least 12 months.
- Applicants must be able to work independently and in a structured manner and have the ability to cooperate with others.
- Applicants must have excellent skills in oral and written English (self-assessed in the CV and demonstrated in the application).
- The application and relevant documents must be in English.
Personal and relational qualities will be emphasized. Research experience, ambitions and potential will also be considered during candidate evaluation.
Special requirements for the position
The University of Bergen is subjected to the regulation for export control system. The regulation will be applied in the processing of the applications.
About the position of postdoctoral research fellow:
The position of postdoctoral research fellow is a fixed-term appointment with the primary objective of qualifying the appointee for work in top academic positions. You cannot be employed as a postdoctoral fellow for more than one fixed term period at the same institution.
The employee may be assigned required duties in the form of teaching and similar work at the department.
The fixed term period for the position is three years, with the possibility of an extension of the period with up to one year if the appointee is granted externally financed research stays abroad.
For all LEAD AI fellows, a Personal Career Development Plan (PCDP) will be developed jointly by the fellow, supervisor, and co-supervisor by the end of Month 3 of the fellowship, including a plan for the individual research budget, and information on additional funding where applicable.
It is a requirement that the project is completed in the course of the period of employment.
We can offer:
- An engaged and professionally stimulating working environment.
- position as postdoctoral fellow (code 1352 in the basic collective agreement) and a gross annual salary of NOK 624 500 upon appointment. Further increases in salary are made according to length of service in the position. For applicants with a medical specialization, salary NOK 657 300. A higher salary may be considered for a particularly well-qualified applicant.
- Welfare benefits* and social benefits including pension-saving in the Norwegian Public Service Pension Fund, occupational injury insurance, full salary during sick leave for 52 weeks, and paid parental leave**.
- Extension of the position term (work contract) due to sick leave and parental leave **.
- Norwegian language courses free of charge.
- High standards for working hours, holidays, place of work, health, and safety.
- Access to specific training activities exclusively provided within the framework of the LEAD AI programme.
*) Subject to membership in the Norwegian National Insurance Scheme. For non-EU outgoing fellows, individual benefit agreement must be considered.
**) Right to paid parental leave requires 6 months paid work before first day of leave. See full requirements.
How to apply:
Before starting the online application process, please familiarise yourself carefully with our application requirements in the Guide for Applicants and Application templates .
It is essential that all required attachments (see next section) are uploaded via our electronic recruiting system JobbNorge. Before uploading any documents in the portal (to minimise repetition of information):
- In the ‘JobbNorge-application field’: Only write your name.
- In the ‘JobbNorge-CV form’: Only fill in your 1) personal details, 2) information about your PhD-degree (in the field ‘Academic qualifications’) and 3) recent relevant work experience.
- You do not need to fill in any other sections in the JobbNorge form, as all the information we need will be provided by you when attaching the mandatory elements listed in the next section.
Your application must include:
- Research proposal (5 pages, using a template based on the evaluation criteria), must be relevant to the AI-related research themes defined by LEAD AI host research groups in the call. It is essential that you discuss the details of the project idea with your potential UiB supervisor at an early stage in the application process, to ensure that there is a match between resources and expertise needed to implement the project.
- A motivation letter.
- A CV detailing the full scientific track record, relevant other achievements and career breaks (e.g., parental, and long-term sick leave, compulsory military service, and non-academic work)
- Mobility declaration with supporting documentation (e.g., employment contract, rental agreement. etc.).
- Table of potential ethics and security issues that might apply to the research proposal (self-assessment).
- An initial self-assessment of opportunities for mandatory and recommended open science practices.
- External host declaration (for outgoing candidates only).
- Scanned copy of the PhD diploma or documentation of formally delivered doctoral thesis (translated to English if necessary; Scandinavian languages are accepted).
- References. Letters of recommendation from the graduating university or previous employers are encouraged.
The application and appendices with certified translations into English or a Scandinavian language must be uploaded at Jobbnorge
Evaluation
We anticipate the whole evaluation procedure to take approximately 4 months from application deadline.
Eligible applicants will be evaluated by three internationally renowned experts and assessed against criteria addressing excellence, impact, implementation, quality of the researcher and training, and
knowledge transfer. Details are stated in the Guide for applicants.
The applicant’s personal suitability for the position is a significant factor in the evaluation.
General information:
For further information please contact:
- Professor Anagha Madhusudan Joshi-Michoel
- For HR related questions contact: Selina Sia Hausberg
Diversity is a strength that enables us to solve our tasks even better. UiB therefore needs qualified employees regardless of gender, ethnicity, religion, worldview, disability, sexual orientation, gender identity, gender expression, and age.
The University of Bergen applies the principle of public access to information when recruiting staff for academic positions.
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.
We encourage applicants with disabilities, immigrant backgrounds, or gaps in their CV to apply.
By indicating such circumstances in your application, you may receive favorable consideration. We ensure that at least one qualified applicant from each of these groups is invited for an interview as part of our commitment to inclusivity and equal opportunity.
Further information about our employment process can be found here.
