Postdoc position in -source respiratory signal analysis; M3RESP
Listed on 2026-03-03
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Science
Research Scientist, Data Scientist, Clinical Research
Location: Netherlands
Organisation/Company University of Twente (UT) Research Field Engineering » Biomedical engineering Engineering » Computer engineering Researcher Profile Recognised Researcher (R2) Final date to receive applications 31 Mar 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure?
No
You will work on the development of M3
Resp, a new open-source FAIR platform for multimodal monitoring of respiratory signals in the Intensive Care setting, including surface EMG (sEMG), electrical impedance tomography (EIT), mechanical ventilator waveforms, and respiratory muscle pressures. This project is a close collaboration between the University of Twente (CRPH - Cardiovascular and Respiratory Physiology group, sEMG expertise center) and the Intensive Care department of the Erasmus MC (ROTARC - Rotterdam Advanced Respiratory Care group, EIT expertise center), two internationally leading institutes in respiratory and mechanical ventilation research.
Open Science NL provides the funding to stimulate open, reusable, community-driven research software. Both institutions provide a full-time position each for the duration of 1 year, and both candidates will closely collaborate with each other and with data researchers in building a sustainable national digital research infrastructure.
By integrating and extending two existing research software packages (ALIVE and ReSurfEMG), you will enable unified data handling, signal processing, and user-friendly GUI-based analyses for clinical and physiological research.
You will combine Python-based software development, biomedical signal processing, and FAIR data design, and contribute to a platform that supports researchers in understanding and analyzing complex respiratory time-series data.
You will merge codebases, implement dedicated data containers, port and optimize signal processing algorithms, build a Dash-based GUI, and develop standardized analysis pipelines. The role includes community-oriented tasks such as documentation, tutorials, and user support. The work requires strong programming skills, experience with time-series data, and an interest in biomedical signals and open-source research software.
- A PhD degree (or equivalent research software engineering degree) in Biomedical Engineering, Technical Medicine, Computer Science, Applied Physics, or a related field;
- Strong software engineering skills in Python, including experience with git, framework design and publishing software; experience with Dash or other GUI frameworks is an asset;
- Experience with signal processing and time-series data, ideally including sEMG or EIT;
- Affinity with FAIR data principles and open-source software development;
- Excellent communication skills, a collaborative attitude, and strong attention to documentation and user support;
- Good communication skills and an excellent command of English.
- A full-time position for 1 year
- Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU).
- You will receive a gross monthly salary ranging from €4241,- to €5538,- based on a full-time position, depending on your experience and qualifications
- There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme.
- A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
- Free access to sports facilities on campus.
Are you interested in this position? Please send your application via the 'Apply now' button below before April 1st and include a CV, motivation and list of publications.
Screening will be a part of the procedure.
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