Research Assistant in “Artificial intelligence in Laser optics” (f/m/d)

12.08.2022, Wissenschaftliches Personal

We are looking for a research assistant (f/m/d) with a Dipl.-Ing. (Univ.) or M.Sc. degree in Computer science, Mechanical engineering, Process Engineering, Mechatronics, Informatics, or related field.

About us
As a globally renowned institute in the field of brewing, beverage, and grain technology, we aim to always be at the forefront of scientific research. The development, implementation, and provision of innovative, forward-looking technologies and concepts in these fields are essential core aspects of our work. We believe that excellent research and lateral thinking will create innovative ideas and solutions for tomorrow's industry.
Integrated into the Chair of Brewing and Beverage Technology is the working group BioPAT and Digitalization, which deals with issues from the fields of PAT technologies, bioprocess analysis, modeling, chemometrics, control engineering, artificial intelligence, soft sensors, and process sensors. We are always looking for new technologies and new methods to monitor and optimize products and processes in real-time.

What we offer
Creative freedom – knowledge development – industrial contacts – young and creative team

Your Tasks
• Scientific work and project management
• Development of experimental setups and Neural Networks
• Publication of results in journals and at conferences
• Collaboration in the teaching activities of the chair
• Collaboration in the acquisition of third-party funding
• Goal is the doctorate

Research topic:
All laser optical methods have in common that coherent light (laser) is applied to the sample and interacts with it. When the laser is applied to a sample containing freely moving particles, random scattering of light occurs both at the surface and in the layers below. Interference effects create a pattern of lighter and darker spots called a speckle. This is recorded and evaluated as a speckle image by a detector (camera). Depending on the laser speckle method used, different features are extracted from the speckle images, and different parameters are calculated. However, the image analysis is limited due to the lack of existing knowledge and complex data evaluation.
Therefore, different laser optical methods for the calculation of single parameters shall be combined in one system and the analysis of the speckle images is to be performed with artificial intelligence (AI) in the form of artificial neural networks. The main scientific task is to interpret the network model and use prior knowledge to develop a reliable and generalized network model. The investigations will focus on the laser-optical characterization of highly concentrated products about their rheological properties and composition.

Requirements
• You are enthusiastic about artificial neural networks
• Understanding of theory and practice of lasers
• Ability and interest in analytical, creative, and interdisciplinary thinking
• High level of initiative and commitment
• Ability to work in a team and communication skills
• Good knowledge of python programming
• Experience with deep learning methods and packages
• Completed university degree

The position will initially be part-time. An increase is possible with appropriate performance. This position is compensated in wages according to the German salary structure for public sector employees (TV-L). TUM is an equal opportunity employer. As such, we explicitly encourage applications from women. Applications from disabled persons with essentially the same qualifications will be given preference.

Application
Please submit your electronic application as a single PDF file and include the reference “Artificial intelligence” in the subject line. For full consideration, apply no later than 30.09.2022 to [email protected]

Contact
Lehrstuhl für Brau-und Getränketechnologie
Weihenstephaner Steig 20
85354 Freising
[email protected]
www.lbgt.wzw.tum.de

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: [email protected]