Student Assistant in The Field of machine Learning
vor 6 Monaten
The Fraunhofer Institute for Digital Media Technology IDMT is part of the Fraunhofer-Gesellschaft. Headquartered in Ilmenau, Germany, the institute is internationally recognized for its expertise in applied electroacoustics and audio engineering, AI-based signal analysis and machine learning, and data privacy and security. At the headquarters, on the campus of “Technische Universität Ilmenau” researchers work on technologies for robust, trustworthy AI-based analysis and classification of audio and video data. These are used, among other things, to monitor industrial production processes, but also in traffic monitoring or in the media context, for example when it comes to automatic metadata extraction and audio manipulation detection. Another focus is the development of algorithms for the areas of virtual product development, intelligent actuator-sensor systems and audio for the automotive sector. There are currently around 70 employees working at Fraunhofer
IDMT in Ilmenau.
The group "Industrial Media Applications" develops machine learning algorithms for acoustic condition monitoring as well as for acoustic event detection in industrial production. These ML algorithms provide the basis of reliable monitoring methods that can be used along the entire value chain.
**What you will do**
- Collaborate with our experienced data scientists and engineers to research and implement machine learning and deep learning algorithms for Predictive Maintenance
- Work on sensor fusion and multimodality techniques to integrate data from various sensors and modalities to enhance predictive maintenance models
- Assist in audio data preprocessing, feature engineering, and model development using Python, TensorFlow, or other relevant tools and frameworks
- Analyze and interpret data to gain insights into equipment health and performance, contributing to our continuous improvement initiatives
- Contribute to the design and implementation of experiments to validate and optimize predictive maintenance algorithms
- Stay up-to-date with the latest advancements in machine learning, deep learning, sensor fusion, and multimodality in Predictive Maintenance
**What you bring to the table**
- Student in a relevant technical discipline (e.g., Computer Science, Data Science, Electrical Engineering, or a related field)
- Strong knowledge of machine learning and deep learning concepts, and experience
- Previous knowledge of audio data analysis and signal processing
- Familiarity with Python and machine learning libraries (e.g., Librosa, Scikit-learn, Keras, TensorFlow)
- Interest in sensor fusion, multimodality, and Predictive Maintenance in Manufacturing
- Analytical mindset with a passion for problem-solving and a drive to learn and explore new technologies
- Excellent communication skills and the ability to work effectively in a team
- Motivation, initiative, flexibility, and willingness to perform
- A strong independence and reliability as well as a thorough way of working
- Enjoying interdisciplinary cooperation and being willing to take on responsibility
- Good communication skills and a convincing appearance
- Analytical, structured and output-driven working style
- Very good knowledge of German and English, both written and spoken
**What you can expect**
- Exciting market-related topics with complex issues to be solved - you can be actively involved in shaping the future
- Challenges at a high level - on top we offer you excellent opportunities for professional and technical trainings
- Space to also implement your own ideas, such as in our quarterly open-topic idea contest
- An excellent technical infrastructure
- Renowned partners and customers who work closely with you to develop the technologies of tomorrow
- A very good work-life balance thanks to flexible working hours, a co-child office, the option of digital childcare in case of daycare shortages, and the possibility of mobile working, because family comes first - we know that
- An open-minded and interested team, a tolerant and familiar atmosphere as well as regular team events
- Good transport connections and proximity to the state capital Erfurt
- Attractive special offers as part of Fraunhofer corporate benefits with numerous enterprise partners
- New work and diversity are not just empty buzzwords, but an integral part of our corporate culture
- An in-house air-hockey table, on the one hand for lunch break, on the other hand it is used to demonstrate our technologies at trade fairs and events
The monthly working time is 40 hours. This position is limited to three months. Remuneration according to the general works agreement for employing assistant staff.
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer hel
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