Researcher in functional precision medicine and cell painting

Norwegian University of Science and Technology (NTNU); Trondheim; On-site; NOK 600,000 - 730,000; Full time

Benefits offered by this job

Employee benefits

Job summary

NTNU in Trondheim invites applications for a two-year researcher position in computational high-content imaging analysis as part of the EP PerMed ERKetype project. The role focuses on analyzing Cell Painting data from cancer models and drug screens, developing reproducible Python workflows, and integrating imaging-derived phenotypes with mechanistic models.

You will work with FlobakLab at NTNU, SINTEF Industry, and clinical partners, leveraging GPU resources (4 × RTX PRO 6000) and contribute to

Qualifications

• PhD or equivalent in bioinformatics, computational biology, or related field.
• Documented experience with high-content imaging analysis.
• Proficient in CellProfiler or similar bioimage software.
• Strong Python programming for scientific data analysis.
• Experience with large-scale data processing and reproducible research.
• Excellent written and oral English.

Responsibilities

• Analyse Cell Painting and high-content imaging data from drug screens.
• Develop and document reproducible Python-based analysis pipelines.
• Integrate imaging-derived phenotypes with multi-omics and clinical data.
• Collaborate with NTNU, SINTEF Industry, and international partners.
• Contribute to publications, reports, and project milestones.

Skills

Python programming

High-content imaging analysis

CellProfiler software

English language skills

Reproducible research practices

GPU computing experience

Education

PhD or equivalent doctoral degree

Tools

CellProfiler

DeepProfiler

GPU-based analysis tools

Job description

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.

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 organisational 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.

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.

NTNU - knowledge for a better world

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

The Department Of Clinical And Molecular Medicine (IKOM)

The Department of Clinical and Molecular Medicine (IKOM) is NTNU’s largest department, with 450 employees. Our research and teaching help to improve treatment and health. IKOM has expertise in basic, clinical and translational research within broad disciplinary areas. We study children’s and women’s health, cancers, blood disorders and infectious diseases, gastroenterology, inflammation, metabolic disorders, laboratory sciences and medical ethics. The Department offers teaching in medicine at master’s and PhD level. We also offer continuing education for employees in the health services.