Ph.D. position in Bioinformatics and Analysis of Next Generation Sequencing Data

Deadline: 29.09.2021

Inland Norway University of Applied Sciences

Inland Norway University of Applied Sciences (INN University) is home to over 14,000 students and 1,000 employees, and has campuses in Lillehammer, Hamar, Elverum, Rena, Evenstad and Blæstad.

INN University aspires to build strong and enduring academic and research environments that will spearhead regionally, nationally and internationally. We are developing a new and better institution with high academic and pedagogical quality, aiming at achieving university accreditation by 2020.

The campus is located in the city of Hamar, an urban region with 80,000 inhabitants. Hamar is located a little over 1 hour from Oslo and less than 1 hour from Norway's main airport. The campus has about 3,000 students and 300 employees. With its stable climate, varied nature, and rich cultural heritage, the region can offer experiences all year round. The location between Lake Mjøsa and the mountain ranges means that everything is suitable for hiking, cycling, golf, fishing, or skiing - either cross-country skiing or alpine skiing.

Our vision is "Stronger Together".

About the position

A 100% Ph.D. position in Biotechnology is available at Inland Norway University of Applied Sciences (INN), Faculty of Applied Ecology, Agricultural Sciences, and Biotechnology (ALB). The position will run for 3-years, starting in January 2022. The candidate will be enrolled in INN’s Ph.D. program in applied ecology and biotechnology, with a workplace at Hamar.

The appointed candidate will be working within a proliferating scientific environment, consisting of academic staff members, Ph.D./Postdoctoral fellows, and students, with scientific expertise ranging from next-generation sequencing (including RNA-seq and metagenomics), bioinformatics, machine learning, and statistics to molecular biology and exercise physiology.

The candidate’s main supervisor will be Associate Professor Rafi Ahmad, and the co-supervisor will be Professor Stian Ellefsen.

The candidate’s main supervisor will be Associate Professor Rafi Ahmad, and the co-supervisor will be Professor Stian Ellefsen.

This position is part of a joint project between the Bioinformatics and Biodiscovery (B&B; ALB Faculty, INN) and the Trainome research groups (Faculty of Health Sciences, INN), led by Ahmad and Ellefsen, respectively. Both the research groups focus on human health, emphasizing solving major global health challenges and corresponding to the UN's goals for sustainable development (# 3: Good health and well-being; # 17 Partnerships for the goals). The research groups are complementary to each other. The Trainome focuses on collecting health data through human interventions with associated analyses, and the B&B focuses on bioinformatics processing and analysis of large and complex health data.

Personalized lifestyle therapy with resistance training represents an intriguing prospect to deal with the apparent lack of responses seen to lifestyle interventions in many individuals, particularly in the chronically diseased. The project involves the processing and analysis of big data and the development of machine learning models. After that, the candidate will develop a proof-of-concept computational model to predict muscle growth responses to given resistance training protocols. In future research, such analyzes will also be important tools for other disciplines, including infection, antimicrobial resistance, and public health scientific data (e.g., epidemiological data). The Ph.D. candidates' competence development and implementation ability are ensured by the research groups' interdisciplinary and complementary competence.

The project involves national and international research collaborations, including Simula Research Laboratories, The Royal Institute of Technology - Stockholm, Indian Institute of Technology -Delhi, and further research collaboration with Inland Hospital and Oslo University Hospital.

For more information about the position, please contact:


The candidate must have a Master’s degree in biotechnology, bioinformatics, biostatistics, molecular biology, or similar subjects, with an average weighted mark for the Master’s degree program of at least a B. However, applicants with a Master's degree with a lower average mark may be admitted after special review.

Required qualifications

  • Experience with analysis of large-scale next-generation sequence data from, especially RNA-Seq, and metagenomics.
  • Experience with mathematical or statistical modeling of biological data.
  • Fluency in scripting in R.
  • Hands-on experience with shell scripting and Linux system.

Desired qualifications

  • Experience with algorithm development and knowledge of machine-learning algorithms is desirable.
  • Experience with scripting in Python.
  • Experience with molecular biological laboratory experiments is an advantage.

The candidate will also have to demonstrate an excellent level of spoken and written English. A further preference will be given to candidates with good teamwork characteristics and communication skills and documented scientific publications or other writing experience.

How to apply

The application and attachments must be submitted electronically and include the following:

  • Application cover letter that summarizes how the candidate’s motivation and how they meet the position requirements.
  • CV (summary of education and work experience).
  • Copies of academic certificates/transcripts.
  • List of minimum 2 references with full contact information.

A complete list of scientific and other publications.

Inland Norway University of Applied Sciences aims to balance gender composition in the workforce and recruit people with ethnic minority backgrounds. According to the Norwegian Law "Offentlighetsloven §25.2 ledd", information about the applicant can be published even if the applicant has requested not to be included in the public list of applicants.

We offer

  • A place in an ambitious and highly international environment.
  • A challenging and exciting project with opportunities for personal and scientific development.
  • An independent and flexible work setting that the successful candidate may, to a large extent, influence her/himself. Daily contact with inspiring skilled colleagues.
  • A campus setting surrounded by forests and mountains with opportunities for outdoor recreation.

Life insurance and occupational injuries 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.

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