Academic Researcher in Visual Computing for Neuroscience

Saarland University is a campus university that is internationally recognized for its strong research programmes. Fostering young academic talent and creating ideal conditions for teaching and research are a core part of the university’s mission. As part of the University of the Greater Region, Saarland University enables students and staff to share and exchange knowledge and ideas between disciplines, between universities and across borders. With over 17,000 national and international students, studying more than a hundred different academic disciplines, Saarland University is a diverse and dynamic learning environment. [Saarland University is officially recognized as one of Germany’s family-friendly higher-education institutions and with a combined workforce of more than 4,000 it is one of the largest employers in the region.]

The Systems Neuroscience & Neurotechnology Unit, Medical faculty is inviting applications for the following position commencing 01 May 2023

Academic research assistant (m/f/x)

Reference number W2234, salary in accordance with the German TV-L salary scale1, pay grade: E13, employment:

100 % of standard working time.

Workplace/Department:

We are looking for an image processing and computer vision researcher to join our team at the Systems Neuroscience and Neurotechnology Unit. You will be working in the interdisciplinary project VI-Screen in collaboration with researchers from TU-Berlin and the Saarland University Clinic, where you will help develop a new system for contactless screening of respiratory infections using a fully calibrated, multimodal camera system.

You will have the opportunity to work with a one-of-a-kind dataset consisting of RGB stereo, NIR and thermal videos, microphone recordings, as well as of laboratory diagnostic detection of the most common viruses and bacterial pathogens, information on the oral microbiome and general, clinical anamnesis. The diagnostic data from the lab and patient anamneses will be used as ground truth for the development and validation of computer vision algorithms. The successful candidate will have the opportunity to contribute to the development of new methods and the potential for scientific publications. The ideal candidate will have experience in computer vision, and knowledge of machine learning and deep learning frameworks, as well as an interest in interdisciplinary research.

Job requirements and responsibilities:

• Development and implementation of methods from machine learning and computer vision with a focus on methods for remote physiological and psychophysiological assessment (rPPG, micro-expressions, …)
• Correlation of lab results with the data from the contactless modalities in cooperation with the project team
• Participation in the implementation of those methods into a real-time system
• Literature research and preparation of scientific publications

Your academic qualifications:

• Completed scientific university studies in visual computing, computer science, math or comparable (M.Sc.) or scientific doctoral degree / PhD

The successful candidate will also be expected to:

• Have experience in the area of visual computing, deep learning or biomedical imaging, backed up with successful projects and publications
• Have very good programming skills in Python, basic programming skills in C++, MATLAB (optional)
• Handon experience with PyTorch and computer vision libraries such as Pillow, opencv, …
• Be interested in interdisciplinary work and has an interest in working on topics that are not their core area of expertise to look at the given problems from different angles
• Be able to work independently on scientific topics and to coordinate requirements in an interdisciplinary team
• Have an interest to compile their results into scientific publications
• Have scientific writing skills in English

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 Plus‘ of the saarVV)

We look forward to receiving your application. Please quote reference number W2234 when applying. Applications must be received by no later than 31 March 2023 and should be sent to the following address:

Email: daniel.strauss@uni-saarland.de

If you have any questions, please contact us for assistance. Your contact:

Herr Philipp Flotho

Systems Neuroscience and Neurotechnology

Tel.: +49 (0)681/ 5867 99079

Email: philipp.flotho@uni-saarland.de

Pay grade classification is based on the particular details of the position held and the extent to which the applicant meets the requirements of the pay grade within the TV-L salary scale. Part-time employment is generally possible.

If you have obtained a foreign university degree, a proof of the equivalence of this degree with a German degree by the Zentralstelle für ausländisches Bildungswesen (ZAB) is needed before hiring. If necessary, please apply for this in time. You can find more information at https://www.kmk.org/zeugnisbewertung.

Unfortunately, neither costs for attending an interview at Saarland University nor costs for any certificate evaluation by the ZAB can be reimbursed in principle.

We welcome applications regardless of gender, nationality, ethnic and social origin, religion/belief, disability, age, and sexual orientation and identity. In accordance with its policy of increasing the proportion of women, the University actively encourages applications from women. Applications from severely disabled persons will be given preferential consideration in the event of equal suitability

When you submit a job application to Saarland University you will be transmitting personal data. Please refer to our privacy notice for information on how we collect and process personal data in accordance with Art. 13 of the Datenschutz-Grundverordnung. By submitting your application you confirm that you have taken note of the information in the Saarland University privacy notice.