via NAV · 9 September 2026 ·10 days ago

Researcher in functional precision medicine and cell painting

NTNU - Norwegian University of Science and Technology
Trondheim
This listing is from NAV
View original listing ↗

This is NTNUNTNU 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-yHCN5QS0About the JobAre 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 positionAnalyse 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 criteriaYou 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 criteriaExperience 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 characteristicsMotivated 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 offerexciting and stimulating tasks in a strong international academic environmentan open and inclusive work environment with dedicated colleaguesfavourable terms in the Norwegian Public Service Pension Fundemployee benefits
Salary and conditionsAs 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 applicationYour 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 thi

The market for this type of role

Similar openings
143
jobs in Trondheim
Full-time
92%
of roles in Norway
Remote possible
1%
of roles
NTNU - Norwegian University of Science and Technology

10 open positions · Gjøvik, Trondheim, Ålesund

📊 Job market · Norway
4,154
active jobs
1.8%
Remote
Ø 4d
avg. online

Frequently asked questions

How many jobs are available in Trondheim?
Currently 143 roles in Trondheim on AlmostHired, across 47 different companies. Our data is updated daily.
Do roles in Norway offer remote work?
1% of roles in Norway allow remote work, either partial or full. To filter specifically for remote positions, use AlmostHired.
How do I know if I match this role?
Upload your CV — our AI compares your profile to the job requirements and gives you a precise match score, with matching and missing skills.