EPFL Master Internship Data Analysis (M/W) 100 %
ROLLOMATIC CAREERS
11.03.2024
Data Analysis (M/W) 100%
The cutting tools necessary for manufacturing smartphones, tablets, aircraft, cars and medical
devices are high-tech products made on high-precision machines with high-performance software.
Rollomatic designs, manufactures, markets, and maintains these production systems worldwide
with nearly 400 employees.
“DATA ANALYSIS TO IMPROVE INDUSTRIAL PROBLEM SOLVING”
- Master student, oriented towards mechanics, micro-engineering and data science looking
for a part-time/full-time position as an intern - Good knowledge in data science environments
- Strong interest in domains such as data analysis, natural language and image processing,
AI, and software development - Motivation for engineering application in the heart of Swiss-made high-precision industry
- Analyze databases in our departments to identify and propose solutions for future challenges
- Develop strategy to set predictive maintenance
- Implementation of these solutions with an adequate framework
- Collaborate with different teams within the company
- This internship project offers you the opportunity to immerse yourself in a unique environment
that combines industrial aspects, the development of data analysis methods and their
implementation - You will be integrated into a team of professional software developers and engineers,
following modern working methodologies - Your research and development work brings significant added value to our customers,
contributing to the improvement of a core domain - Finally, this research work can possibly continue with a Master thesis, PhD project or
employment at Rollomatic
- Your workplace will be shared between Rollomatic Headquarter (Le Landeron) and one of
our innovation cells: EPFL Innovation Park or Swiss Innovation Park Biel/Bienne - Partial remote work possible
Application deadline: 31.05.2024
Are you interested in this challenge? Please send your application (EN or FR) at:
Write an email
OCT 2023-OCT 2024
CH
Apply independently of a specific job with an unsolicited application.