Hybrid Working Student – Condition Monitoring, Embedded AI

at Fraunhofer IIS

• Job title: Working Student – Condition Monitoring, Embedded AI
• Job type: Part Time
• Experience level: Entry level
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Python
• Location requirements: Hybrid, Nurnberg, Germany

About the role

• Werkstudent*in in der Forschungsgruppe » Efficient AI « am Fraunhofer-Institut für Integrierte Schaltungen. Entwicklung von Künstlicher Intelligenz (KI) für eingebettete Systeme mit Flexibilität im Stundenumfang.

Responsibilities

• In our research group "Efficient AI" we develop artificial intelligence (AI) for embedded systems.
• We rely on a high degree of automation to implement a wide range of use cases as quickly as possible.
• We develop solutions for practical industrial applications in computer vision, sensor data processing, and radio-based localization.
• You will research the latest methods in unsupervised machine learning for sensor data.
• You will investigate and compare approaches for implementing and optimizing AI.
• You will independently implement practical solutions for demonstrators on embedded hardware.
• You will prepare your findings in engaging presentations for the team.

Requirements

• You are enrolled in a Master's program in Computer Science, Data Science, Electrical Engineering, or a related field.
• You have experience with Python and ideally also C.
• You have initial experience with machine learning and AI.
• You are interested in AI for embedded systems and want to develop further in this area.
• You enjoy applying theoretical knowledge to practical problems.

Benefits

• Shape your schedule: Benefit from flexible working hours that fit well with your studies.
• Join a creative team: Experience an open and collegial working atmosphere where your ideas are valued.
• Variety that inspires: Look forward to diverse tasks that challenge and inspire you.
• Help shape the future: Contribute to application-oriented research and put your theoretical knowledge into practice.
• Exciting innovations: Work on interesting, forward-looking projects that make a real difference.