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About the role
We are looking for an Working Student to support the development of digital infrastructure concepts for industrial drilling systems. The focus of the role is to understand how machine and process data are generated in a PLC-controlled drilling setup, how these data should be structured and stored, and how they can be transferred into OEM-side systems for further use.
The Working Student will support work at the interface of manufacturing, automation, and data engineering. A key objective is to enable structured, usable, and traceable drilling data that can support process analysis and performance monitoring.
Job details:
The Working Student will be 80 of working time at the Technical University Munich and 20 at the Boeing Munich Office.
Working Hours: 20h per week during semester and 40h per week during semester break.
Contract Duration: 6 months.
Position Responsibilities:
Support the analysis of a PLC-controlled drilling setup in a supplier environment
Help identify relevant metadata to be captured during drilling operations
Support the definition of a suitable data model for storage, traceability, and later analysis
Contribute to concepts for data flow from the supplier-side machine environment to OEM-side infrastructure
Help assess how the digital setup can be aligned with OEM requirements for integration and data handling
Support the preparation of structured data for downstream analysis and generation of process-related metrics
Assist in documenting interfaces, information flow, and technical requirements for future implementation
Basic Qualifications (Required Skills/Experience):
Preferred Qualifications (Desired Skills/Experience):
Currently enrolled in a Master’s program in Mechanical Engineering, Aerospace Engineering, Manufacturing / Production Engineering, Electrical Engineering, Mechatronics, or a related field
Strong interest in digital manufacturing, industrial automation, and data-driven production systems
Basic understanding of industrial control systems, PLCs, or machine automation
Familiarity with handling technical datasets, including process data and metadata
Ability to think across system interfaces, from machine-level data generation to higher-level data usage
Structured, analytical, and self-driven way of working
Experience or academic exposure in one or more of the following areas is beneficial:
Industrial communication and connectivity
Data acquisition from machines or production systems
Python or similar tools for data handling and analysis
Manufacturing process monitoring
Database concepts, data structuring, or traceability in production environments
Siemens-based automation environments
Conflict of Interest:
Successful candidates for this job must satisfy the Companys Conflict of Interest (COI) assessment process
Applications for this position will be accepted until Apr. 27, 2026
Export Control Requirements:
This is not an Export Control position.
Relocation
Relocation assistance is not a negotiable benefit for this position.
Visa Sponsorship
Employer will not sponsor applicants for employment visa status.
Shift
Not a Shift Worker (Germany)
Equal Opportunity Employer:
We are an equal opportunity employer. We do not accept unlawful discrimination in our recruitment or employment practices on any grounds including but not limited to; race, color, ethnicity, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military and veteran status, or other characteristics covered by applicable law.
We have teams in more than 65 countries, and each person plays a role in helping us become one of the world’s most innovative, diverse and inclusive companies. We are proud members of the Valuable 500 and welcome applications from candidates with disabilities. Applicants are encouraged to share with our recruitment team any accommodations required during the recruitment process. Accommodations may include but are not limited to: conducting interviews in accessible locations that accommodate mobility needs, encouraging candidates to bring and use any existing assistive technology such as screen readers and offering flexible interview formats such as virtual or phone interviews.
