Internship in Machine Learning Research

Stellenbezeichnung: Internship in Machine Learning Research

Firma: Zeiss

Arbeitsort / Location: Oberkochen, Baden-Württemberg

Job Beschreibung: Step out of your comfort zone, excel and redefine the limits of what is possible. That’s just what our employees are doing every single day – in order to set the pace through our innovations and enable outstanding achievements. After all, behind every successful company are many great fascinating people.

In a spacious modern setting full of opportunities for further development, ZEISS employees work in a place where expert knowledge and team spirit reign supreme. All of this is supported by a special ownership structure and the long-term goal of the Carl Zeiss Foundation: to bring science and society into the future together.

Join us today. Inspire people tomorrow.

Diversity is a part of ZEISS. We look forward to receiving your application regardless of gender, nationality, ethnic and social origin, religion, philosophy of life, disability, age, sexual orientation or identity.

Apply now! It takes less than 10 minutes.

Want to drive the next generation of intelligent products? We are seeking passionate and talented students who want to make an impact by helping to develop next generation products and innovative machine learning algorithms at ZEISS. Integrated in a fast-growing team of scientists and research engineers, you will work (for at least 3 months) on helping us to develop core algorithms and taking academic ideas into working prototypes.

a bachelor’s degree in computer science, mathematics, physics, or related fields with an outstanding study record, and are currently enrolled at a university

a solid understanding of machine learning and computer vision

a solid programming background in Python and hands-on experience with machine learning frameworks such as PyTorch or Tensorflow

high motivation, creativity, flexibility, and a structured and independent way of working

effective communication and presentation skills

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