Student Assistant
vor 1 Monat
**for Sensor Technology and Data Science in sustainable Recycling Processes**:
**Contact**:
**Name**:
Zhihong Dou
**Telephone**:
- workPhone- +49 241 80-22772***:
**Institution**:
Lehrstuhl für Anthropogene Stoffkreisläufe und Institut für Aufbereitung, Kokerei und Brikettierung
**Our Profile**:
ANTS searches and analyses in research and teaching for solutions and methods to make anthropogenic material flows recyclable. Thus, we aim to develop raw material management at the product and material level as well as to demonstrate and to implement it by means of practical examples. With its previous expertise, the department is one of the leading research institutions in Europe in the field of mechanical and sensor-based processing technology. The ANTS combines the modelling and evaluation of processing and recycling processes with a view to entire product systems and life cycles in the sense of a circular economy and complements this expertise by technical implementation and demonstration. We offer:
- Collaboration in an exciting and cutting-edge research field
- Involvement in the active processing of research projects
- Flexible working hours and mobile working e.g., during exam preparation
- Extensive supervision and support
- Opportunity to participate in scientific publications as a co-author
- A friendly working environment and occasional team events
In this context, the research group "Sensor Technology & Data Science" investigates possible optimization potentials of sensor-based sorting as well as the extended process control. Our strengths lie in the following areas:
- Access to extensive technical equipment for test campaigns: laboratory, pilot plant, measuring stands for sensor-based sorting and characterization, execution of measurement campaigns in large-scale sorting and processing plants
- Comprehensive assessment of processing technology issues
- Analysis of process chains of mechanical and sensor-based processing
- Quantitative characterization of anthropogenic material systems using inline sensor technology in combination with machine and deep learning algorithms
- Control of separation processes based on relevant parameters such as volume or material composition per time unit
We are looking for a student assistant to strengthen our research group "Sensor Technology & Data Science".
**Your Profile**:
- Enrolled in an engineering or technical/scientific degree program, e.g., Computer science, environmental engineering, mechanical engineering, automation engineering
- Knowledge of or high interest in machine learning and/or computer vision
- Programming knowledge in Python (or high interest in learning it)
- Prior knowledge in sensor technology, raw material and recycling, or mechanical processing desirable, but not mandatory
- Analytical thinking and ability to think abstractly
- Interest in material cycles and life cycle analysis
- High motivation and good communication skills
- Ability to work independently and willingness to work in a team
- Very good knowledge of the MS Office package, especially Excel
- Advanced knowledge of written and spoken English
**Your Duties and Responsibilities**:
- Collaboration in the research project "ORAM": You will develop with us a modular mechanical reprocessing method for the recovery of high-performance polymers from end-of-life aircraft components, so that the plastic recyclates produced can be used again in aircraft-related additive manufacturing. As part of the process development, the technical feasibility of polymer and foreign material detection using near-infrared or X-ray transmission (XRT) sensor technology will be investigated.
- Collaboration in the research project "ProSim": You will support us in the process modeling and simulation of mechanical processing and sorting plants based on sensor-based data. This includes the acquisition of this data in laboratory, pilot plant and plant scale, the preprocessing of data, as well as the modeling of individual processes of transfer functions and representation of the entire process chains.
- Support our scientific staff by independently conducting literature research, preparing and analyzing experimental data, and creating scientific figures.
Assist the Institute with general duties as they arise.
**What We Offer**:
The position is to be filled at the earliest possible date and offered for a fixed term of initially 3 months.
A longer employment is prefered.
This is a part-time contract position.
The standard weekly hours will be 8 hours.
The salary is based on the RWTH Guidelines for Student and Graduate Assistants.
The position corresponds to a pay grade of 12,00 € per hour.
**About us**:
RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have acces
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