This is NTNU

NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You can find more information about working at NTNU and the application process here.

   

Video: https://youtu.be/Xt-yHCN5QS0

About the Job

Are you excited by the possibility of turning cellular imaging, drug-response data and cancer biology into better treatment predictions for individual patients? We have a two-year position for a researcher in computational high-content imaging analysis as part of the international EP PerMed project ERKetype.

ERKetype aims to develop digital twins as complex biomarkers for precision cancer medicine, with a particular focus on cancers driven by dysregulation of the RAS/RAF/MEK/ERK signalling pathway. The project combines patient-derived cancer models, Cell Painting and other high-content imaging approaches, pharmaco-proteomics, multi-omics data, artificial intelligence and mechanism-based modelling to understand why cancer cells respond — or fail to respond — to targeted therapies.

The researcher will be part of FlobakLab at NTNU (www.flobaklab.com), an interdisciplinary precision oncology group with expertise in both wet- and dry-lab research. In this position, you will play a central role in analysing Cell Painting and high-content imaging data from drug screens in cancer cell lines, patient-derived cancer organoids and patient-derived tumouroids. You will work closely with SINTEF Industry and its robotic high-throughput drug-screening facilities. The researcher will also have access to FlobakLab’s dedicated GPU workstation, equipped with 4 × RTX PRO 6000 Max-Q GPUs and supported by NVIDIA. Your work will include developing reproducible Python-based analysis pipelines, extracting and interpreting morphological drug-response signatures, and developing and implementing approaches to integrate imaging-derived phenotypes with mechanistic and knowledge-driven modelling frameworks.

This is an opportunity to work at the interface between computational biology, cancer systems medicine and translational precision oncology. You will collaborate closely with experimental, computational and clinical partners in Norway and internationally.

The position is well suited for a motivated researcher who wants to develop advanced imaging-data methods and apply them to clinically relevant questions in personalised cancer medicine.

Your immediate leader is Professor Åsmund Flobak.

Duties of the position

• Analyse Cell Painting and other high-content imaging data from drug-screening experiments in cancer cell lines, patient-derived cancer organoids and patient-derived tumouroids.
• Develop, run and document reproducible image-analysis workflows, including CellProfiler-based segmentation, feature extraction, image quality control and metadata handling.
• Develop Python-based pipelines for preprocessing, normalisation, batch correction, quality control, statistical analysis, visualisation and interpretation of large-scale imaging and drug-response datasets.
• Extract and interpret morphological drug-response signatures, including single-cell and population-level phenotypic profiles.
• Contribute to identification of phenotypic mechanisms of action from perturbation screens and link these to drug response, cancer biology and signalling pathway activity.
• Evaluate and implement advanced computational approaches for high-content imaging analysis, including cytomining workflows and, where relevant, CNN-based methods such as DeepProfiler or related deep-learning approaches.
• Integrate imaging-derived phenotypes with other data modalities, such as drug-response data, pharmaco-proteomics, genomics, transcriptomics and clinical or model metadata.
• Develop and implement approaches for connecting Cell Painting-derived phenotypes with mechanistic and knowledge-driven modelling frameworks, including Boolean, logic-based or related digital-twin modelling approaches.
• Work closely with SINTEF Industry and its robotic high-throughput drug-screening facilities, as well as experimental, computational and clinical collaborators at NTNU and partner institutions.
• Contribute to data management, documentation, reproducible research practices and sharing of analysis workflows and results within the ERKetype consortium.
• Contribute to scientific publications, conference presentations, project deliverables and reports.
• Contribute to coordination of NTNU’s scientific activities in ERKetype, including follow-up of relevant milestones, deliverables, consortium meetings and reporting.
• Contribute to supervision and mentoring of PhD candidates, medical research students and other junior researchers where relevant.

Required selection criteria

• You must have a PhD or equivalent doctoral degree in a relevant field, such as bioinformatics, computational biology, biomedical engineering, image analysis, systems biology, cancer biology, biotechnology, computer science, or a closely related discipline.
• Documented experience with analysis of high-content imaging, Cell Painting, microscopy-based screening data, or other quantitative biological image data.
• Good working knowledge of CellProfiler or closely related bioimage-analysis software.
• Strong programming skills in Python for scientific data analysis.
• Experience with processing, quality control, statistical analysis, visualisation and interpretation of large biological datasets.
• Experience with reproducible research practices, including documentation of code, analysis workflows and results.
• Excellent written and oral English language skills

Preferred selection criteria

• Experience with Cell Painting, morphological profiling, cytomining, high-content screening or microscopy-based drug-screen analysis.
• Experience with analysis of drug-response data from cancer cell lines, patient-derived organoids, tumouroids or other advanced cancer model systems.
• Experience with Python-based workflows for large-scale image-data analysis, including feature extraction, quality control, normalisation, batch correction, dimensionality reduction, clustering or classification.
• Experience with CNN-based, deep-learning or other machine-learning approaches for bioimage analysis, for example DeepProfiler or related frameworks.
• Experience with integration of imaging-derived features with other data modalities, such as drug-response data, genomics, transcriptomics, proteomics, phosphoproteomics, CyTOF or clinical data.
• Experience with mechanism-based or knowledge-driven modelling, such as Boolean modelling, logic modelling, network modelling, ODE-based modelling, model personalisation or digital-twin approaches.
• Knowledge of cancer biology, precision oncology, pharmacogenomics, patient-derived cancer models or RAS/RAF/MEK/ERK signalling.
• Experience with reproducible research practices, version control, workflow management, high-performance computing, GPU-based analysis or containerised analysis environments.
• Experience from interdisciplinary or international research projects involving experimental biologists, computational scientists, clinicians or industry partners.
• Experience with scientific writing, project reporting, deliverables or coordination of collaborative research activities.
• Good written and oral Norwegian language skills

Personal characteristics

• Motivated by interdisciplinary research at the interface between computational biology, cancer biology and precision medicine.
• Analytical, structured and quality-oriented.
• Able to work independently, take initiative and drive tasks forward.
• Collaborative and communicative, with the ability to work well with experimental, computational and clinical partners.
• Curious and willing to learn new methods and technologies.
• Reliable and organised, with the ability to balance scientific work with project deliverables and deadlines.

We offer

• exciting and stimulating tasks in a strong international academic environment
• an open and inclusive work environment with dedicated colleagues
• favourable terms in the Norwegian Public Service Pension Fund
• employee benefits

Salary and conditions

As a researcher (code 1109) you are normally paid from gross NOK 600 000 to NOK 730 000 per annum before tax, depending on qualifications and seniority. As required by law, 2% of this salary will be deducted and paid into the Norwegian Public Service Pension Fund.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU.   

After the appointment you must assume that there may be changes in the area of work. 

For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis. 

About the application

Your application and supporting documentation must be in English. 

The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in English.

Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request.

If, for any reason, you have taken a career break or have had an atypical career and wish to disclose this in your application, the selection committee will take this into account, recognizing that the quantity of your research may be reduced as a result.

Your application must include:

• CV, diplomas, and certificates
• Academic works – published or unpublished – that you wish to be considered during assessment of your application (up to 8 items)
• A description of the scientific/artistic works you consider most relevant, which you particularly wish to be factored into the assessment
• A complete publication list
• A research plan
• Details of projects for which you have served as project manager, including information on financing, duration, and scope
• Names and contact information for three relevant referees

It is important that you both document and reflect on your competence. You are encouraged to use the NTNUs competence matrix as a guide for  documentation of your competence.

Joint work will also be considered. If it is difficult to identify your specific input to a joint project, you must include evidence of your contributions. 

In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal and interpersonal qualities. Motivation, ambitions, and potential will also count in the assessment of the candidates. Open scientific practice will be recognized.

NTNU is obliged by the evaluation criteria for research quality in accordance with The San Fransisco Declaration on Research Assessment – DORA and The obligations in the Coalition for Advancing Research Assessment ( CoARA) on responsible assessment of research and recognition of a wider range of academic contributions to science and society. This means that we will pay particular attention to the quality and academic range demonstrated by your scientific work to date. We will also pay attention to research leadership and participation in research projects. Your scientific work from the last five years will be given the most weight.

Your application will be considered by a committee at the department. Candidates of interest will be invited to an interview.

General information

Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is Knowledge for a better world and our values ​​are creative, critical, constructive and respectful. We believe that an organization that is equal, diverse, and gender-balanced is essential for us to achieve our goals.   

We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.  

If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability, and cultural background, or whether you have been out of work for a period of time. 

At NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality.

As an employee at NTNU, you must continually maintain and improve your professional development and be flexible regarding any organizational changes.

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the reservation is not accepted.

For the sake of transparency, candidates will be given expert evaluations of their own and other candidates. As an applicant you are considered part of the process and are stipulated by rules of confidentiality. 

If you have any questions regarding the position, please contact Professor Åsmund Flobak, tel. 0047 72 57 37 17, e-mail asmund.flobak@ntnu.no. 

If you have questions regarding the recruitment process, please contact HR Advisor Sissel Sollien, e-mail sissel.sollien@ntnu.no

Application deadline: 25.09.2026

Located in central Norway, Trondheim is a dynamic and forward-looking city known for its strong research, technology, and innovation ecosystem. With a population of around 200,000, the city combines the advantages of urban living with easy access to nature. Residents benefit from Norway’s high standard of living and comprehensive welfare system, including excellent healthcare, education, and affordable childcare. Trondheim offers a vibrant cultural scene, outstanding opportunities for families, including international schools, and a safe and welcoming community with low crime rates, clean air, and easy access to outdoor activities year-round.