At the core of Siemens’ business are complex software-intensive systems that communicate and control information or processes. The enhancement of these systems spreads across all industry domains. The Software Systems and Processes (SSP) technology field contributes to these enhancements and drives innovation to improve current and shape future business.
Our research group for Architecture and Verification for Intelligent Systems (AVI) is looking for an intern that can contribute to the teams complex systems architecture. As a team member you will tackle challenges identified in the area of complex and intelligent systems through discussions, implementation, and tests. Your internship will consist of one dedicated topic for which you will have the possibility to contribute with your expertise and collaborate with the team to drive the success of the topic.
The topic for this internship is about using machine learning techniques to benchmark the maintainability of code. Using this technique, we aim to understand the impact of certain coding guidelines and help devise new ones that a Siemens business unit can use.
During this internship, you will:
- Utilize mining software repository techniques to mine source code of differing quality levels from open source and industrial projects
- Train different NL based models to measure maintainability of source code
- Understand the impact of different coding guidelines that Siemens teams use
- Define coding guidelines that lead to the best maintainability
Qualified candidates will have/be:
- A current student pursuing a MS/PhD degree in Computer Science / Software Engineering
- Solid software development skills
- Good ability in mining source code from GitHub/GitLab
- Good understanding of static analysis tools and source code metrics
- Good understanding and knowledge of training large NLP models
- Good knowledge of English (spoken and written)
- Where permitted by applicable law, Siemens may require employees to be fully vaccinated against COVID-19 based on job requirements, and in accordance with an accommodation based on legally protected reasons
Siemens Technology employees are passionate about applied research. We create technology with purpose that benefits society - more agile and productive factories, more intelligent and efficient buildings and grids, more reliable and sustainable transportation. Our work powers Siemens products and is regularly featured in patents and publications. We operate in a global ecosystem focused on innovation, partnering with our customers, businesses, government agencies, and leading academic institutions on highly visible projects where collaboration is key.
Our people continuously develop their talents, are curious, and are not afraid to take risks in pursuit of technological innovation. A strong learning culture empowers employees at Siemens Technology to own their growth and development.
We know that diversity fuels innovation and drives business success. We are committed to creating an inclusive environment, where diversity of thought, culture, and experience is seen as our greatest strength. This is what brings our best ideas to life.
We take pride in bringing our best selves to work every day, prioritizing individual health, work-life blend, and flexibility.
At Siemens Technology, the success of our employees drives our success.
Company: Siemens Corporation
Experience Level: Student (Not Yet Graduated)
Job Type: Full-time
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