Student Assistant / Intern in the field of machine learning (IOF-2023-88)

The Fraunhofer – Institute for Applied Optics and Precision Engineering IOF in Jena conducts applied research in the field of photonics and develops innovative optical systems to control light – from its generation and manipulation to its application. The services offered by the institute cover the entire photonic process chain ranging from opto-mechanical and opto-electronical system design to the manufacturing of customer-specific solutions and prototypes.

The project group SILIQUA (“Silicon-based Photonic Building Blocks for On-Chip Lighting, Modulation, Sensing and Quantum Applications”) at the Fraunhofer IOF deals with active silicon photonics, in particular the functionalization of silicon resonators with electro-optically active coatings or defects. Nanoscopically modulatable photonic silicon resonators are developed for integration into prototype photonic silicon LEDs, lasers, quantum light sources, modulators or chip-level sensors. In the process, the design and fabrication of the resonator structures are optimized using machine learning methods.

To support the SILIQUA project group, we are looking for a research assistant to develop algorithms for data analysis using machine learning methods. The work can be linked to data generation in current experiments or optical simulations of the group. Within the scope of the job there is the possibility to write a thesis (Bachelor and Master).

What you will do

• Creation of source codes for data analysis with the help of machine learning methods
• If necessary, generation of data sets in experimental setups or simulations for current projects
• Using the results to further develop measurement methods or components
• Collaboration with multinational teams
• Documentation of the results in theses or publications

What you bring to the table

• Student of physics, materials science, laser and optotechnologies, engineering, ophthalmic optics or a related field of study.
• Good knowledge of the Python programming language
• Experience with machine learning methods and GitHub version management is an advantage
• Great interest in the above mentioned subject area
• Independent, flexible and reliable way of working, creative and analytical thinking, as well as team orientation and communication skills
• Friendly, reliable and open manner​

What you can expect

• Gain valuable practical experience during your studies in the context of exciting research projects 
• Collegial, open-minded and friendly 
• Varied task in laboratories with modern equipment
• Networking with first-class industrial partners and research groups
• Comprehensive professional guidance and support from scientific mentors
• Flexible working hours to combine study and practice
• Very good connection to public transport

We value and promote the diversity of our employees’ skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. 

The weekly working time is 39 hours when writing a thesis or completing an internship. In the case of student assistantships, this is agreed on an individual basis. Depending on the employment relationship, remuneration is based on the general works agreement on the employment of scientific assistants or on the federal guidelines for interns’ remuneration. The position is limited. We are looking for a long-term corporation.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future. 

Interested? Apply online now. We look forward to getting to know you!

Fraunhofer Institute for Applied Optics and Precision Engineering IOF 

www.iof.fraunhofer.de  

Requisition Number: 68514                Application Deadline: 10/03/2023