You will enhance existing models to improve the efficiency of processing high-dimensional temporal data, conduct research, design new extensions, and evaluate their performance for real-time applications.
Anforderungen
- •Master's degree in Natural Sciences
- •Strong knowledge in Machine Learning
- •Experience in Deep Learning
- •Experience in Computer Vision
- •Proficiency in Python (PyTorch)
- •Strong intrinsic motivation
- •Ability to work independently
- •Fluent in English
Deine Aufgaben
- •Develop a temporal predictive extension of foundation models.
- •Identify and eliminate redundancy in high-dimensional temporal data.
- •Conduct a comprehensive literature review on current methodologies.
- •Design a novel model extension with temporal predictive capabilities.
- •Implement training protocols to optimize model performance.
- •Evaluate model efficiency regarding computational and energy consumption.
- •Analyze findings' implications for real-time AI applications.
Original Beschreibung
## Job Description
The goal of this master thesis is to explore innovative methodologies for enhancing the efficiency of deep neural networks in artificial intelligence applications, particularly in robotics and autonomous driving.
* During your thesis you will work on developing a temporal predictive extension of existing foundation models to identify and eliminate redundancy in temporal high-dimensional data, such as video streams. This approach aims to significantly reduce runtime inefficiencies associated with sequential computations, thereby streamlining the inference process and improving overall model performance.
* You will conduct a comprehensive literature review to understand current methodologies.
* Furthermore, you will design a novel model extension that incorporates temporal predictive capabilities, and you will implement training protocols to optimize the model's performance on temporal data.
* Finally, you will evaluate the model's efficiency in terms of computational and energy consumption and analyze the implications of the findings for real-time AI applications.
## Qualifications
* **Education:** Master studies in the field of Natural Sciences and Engineering (like Computer Science, Math, Statistics, Physics, Cybernetics, Electrical Engineering) with very good grades
* **Experience and Knowledge:** strong knowledge and experience in Machine Learning, Deep Learning, Computer Vision, and Python (PyTorch)
* **Personality and Working Practice:** you excel at working independently and driving your own projects forward with strong intrinsic motivation
* **Languages:** fluent in English
## Additional Information
**Start:** according to prior agreement
**Duration:** 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.
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