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Student Position: Advanced Data Analysis
vor 2 Monaten
Company Overview: Infineon Technologies is a leading global semiconductor company specializing in power systems and IoT solutions. Our innovations drive sustainable energy, secure mobility, and intelligent IoT applications.
Position Summary: We are seeking a dedicated working student to contribute to the development of a customizable foundation model tailored for various vision tasks utilizing Infineon's unique dataset.
- Key Responsibilities:
- Develop a foundation model that can be tailored for diverse vision applications using Infineon's dataset.
- Work on a model that accommodates images of varying sizes and spatial resolutions, leveraging spectral information to surpass existing models.
- Engage with Infineon's distinctive dataset, which significantly diverges from conventional image datasets.
- Optimize the model to effectively utilize spectral data, drawing inspiration from advanced models such as DINOv2 and Mask Auto Encoder (MAE).
- Investigate multi-stage pretraining techniques to enhance model performance.
- Validate model performance through ablation studies and comparisons with established foundation models.
Qualifications:
- Currently enrolled in a degree program in Data Science, Electrical Engineering, Informatics, or a related field.
- Familiarity with foundation models, including Segment Anything and Masked Auto Encoder (MAE).
- Strong communication and presentation skills, coupled with analytical and problem-solving abilities.
- Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow or PyTorch.
- Knowledge of Bash scripting and Linux terminal operations to facilitate data processing and model training.
- Good command of English, both written and spoken.
Application Requirements:
- CV in English
- Certificate of enrollment at university
- Latest grades transcript (not older than 6 months)
- High school report
Important Information:
- This is a part-time position, with a maximum of 20 hours per week during the lecture period.
- Applicants must be enrolled and have not completed their examination results or modules, allowing for at least 6 months of collaboration.
- Proximity to the site is essential for regular on-site collaboration and team integration.
Benefits:
- Coaching and mentoring opportunities
- Extensive training offerings and career development planning
- International assignment possibilities
- Diverse career paths: Project Management, Technical Ladder, Management & Individual Contributor
- Flexible working conditions and home office options
- Part-time work availability, including during parental leave
- Sabbatical options
- On-site social counseling and health promotion programs
- Access to an on-site canteen and private insurance offers
- Wage payment during sick leave and corporate pension benefits
- Flexible transition into retirement and performance bonuses
- Accessibility features for individuals with disabilities
- Remote work possibilities from abroad (EU)
