Link to job offer

Workplace/Department:
Academic research assistants and PhD students receive a full position with a salary according to collective agreement for the public sector in Germany (TV-L, E13) which corresponds to a gross salary of approximately 59.000 Euro in the first year and 63.000 Euro in the second and third year.

The Lab for Measurement Technology (LMT), chaired by Prof. Schütze, is a world leading research group in smart sensor systems bringing together expertise in microsensor operation, read-out, and calibration with extensive know-how in machine learning (ML). The Chair consists of two research groups, one focusing on gas sensing technologies and one on multimodal smart sensing.
The research group Gas Sensing Technology is focusing on the development of innovative multimodal system solutions, calibration and calibration strategies, evaluation algorithms based on machine learning and the associated Design of Experiment. These low-cost sensor systems are used for monitoring volatile organic compounds (VOC) and other volatiles at trace levels for various applications including indoor air quality (IAQ), breath analysis and drug monitoring, food quality as well as odor assessment of recycling products. We have strong competence in system characterization and calibration as well as calibration transfer.
In the division of Multimodal Smart Sensing, we focus on the development of automatic machine learning methods in order to extract the desired, physically interpretable information from complex sensor patterns from a wide variety of sensor modalities. The main fields of application are quality control, environmental and safety technology, renewable energies / energy efficiency and condition monitoring of mechatronic systems.
Currently, twelve PhD students, one post-doc and one lab engineer are working for the Chair.
The offered position is affiliated with the research group Gas Sensing Technology (Dr. Christian Bur) but with strong collaboration to the Multimodal Smart Sensing group.

Job requirements and responsibilities:

We are offering a PhD position in smart gas sensing technologies for digital health. The position is linked to the three-year international project SensorTech4Health, coordinated by Bosch Sensortec. Position is subject to the final approval of the project.
The ideal candidate is an excellent, self-driven, and curious problem-solver. A master’s degree in engineering (preferably systems, electrical or bio-medical engineering), or physics, or related disciplines, and a solid foundation in sensors, systems, and data evaluation is required.
Experiences with chemical gas sensors, calibration, and machine learning are recommended.
The job as researcher and PhD student involves:
• Characterization of novel gas sensing layers with reference gas mixtures in the lab
• Development of multimodal sensor systems measuring indoor air quality and body emissions, incl. skin emissions
• Data evaluation using advanced machine learning methods in a Matlab (or Python) framework
• Writing of scientific publications
• Presenting and defending your research at international conferences
• Supporting the acquisition of new research projects
• Participation in teaching activities including supervision of thesis workers (B.Sc./M.Sc.)

Your academic qualifications:
• Completed scientific university studies in systems, electrical or bio-medical engineering, physics, or related disciplines
• Language skills (according to GER): English -C1

The successful candidate will also be expected to:
• Outstanding academic achievements and above-average graduation
• High level of motivation and curiosity, and ability to perform self-driven research
• Programming skills in Matlab and/or Python
• Extensive experience in working in a lab, incl. design of experiments, and data analysis
• Expertise in one or more of the following fields:
   – Gas sensors (e.g. MOS/MOX sensors, FETs, CP, optical)
   – Dynamic operation (e.g. temperature modulation, light excitation, electrical impedance spectroscopy)
   – Sensor arrays (“e-noses”)
   – Electrical engineering: hardware development, PCB design, analog signal processing
   – Micro controller programming
   – Machine learning, deep learning, AI, explainable AI
   – Feature extraction and feature engineering
   – Sensor and data fusion, application specific signal processing
   – Analytical chemistry (e.g. GC-MS, IMS, PTR-MS)
   – Bio-medical engineering
   – Sleep monitoring

• Language skills (according to GER): German B2

What we can offer you:
• A flexible work schedule allowing you to balance work and family, among other things the possibility of teleworking
• Secure and future-oriented employment with attractive conditions
• A broad range of further education and professional development programmes (for example language courses)
• An occupational health management model with numerous attractive options, such as our university sports programme
• Supplementary pension scheme (RZVK)
• Discounted tickets on local public transport services (‘Job-Ticket‘ of the saarVV)
• Job bike leasing (JobRad)

We look forward to receiving your meaningful online application (in a PDF file) by 10.04.2026 to c.bur@LMT.uni-saarland.de. Please include the reference number W2824 in the subject line of the e-mail.

If you have any questions, please contact us for assistance. Your contact:
Christian Bur
Lab for Measurement Technology
www.LMT.uni-saarland.de
c.bur@LMT.uni-saarland.de
phone: +49 681/302-2256