Research Scientist
vor 4 Stunden
Job Summary: We are seeking a highly skilled Research Associate to join our team at Universität Hamburg. The successful candidate will be responsible for conducting research and teaching in the field of multimodal Large Language Models, with a focus on human robot interaction.
Key Responsibilities:
- Conduct research in multimodal Large Language Models and human robot interaction
- Teach and develop courses in robotics and AI
- Collaborate with the research group on technical aspects of multimodal systems
- Pursue further academic qualifications, including a doctoral dissertation
Requirements:
- Master's degree in Computer Science or a related field
- Extensive programming knowledge in ROS, C++, C, Python, Pytorch, Keras, and Tensorflow
- Practical experience with NVIDIA clusters of GPUs, such as H100
- Good knowledge of English (written and oral)
- Ability to work in a team and confident presentation skills
What We Offer:
- Reliable remuneration based on wage agreements
- Continuing education opportunities
- University pensions
- Attractive location
- Flexible working hours
- Work-life balance opportunities
- Health management
- 30 days of vacation per annum
About Universität Hamburg: Universität Hamburg is one of the strongest research educational institutions in Germany. Our work in research, teaching, educational and knowledge exchange activities is fostering the next generation of responsible global citizens ready to tackle the global challenges facing us. Our guiding principle 'Innovating and Cooperating for a Sustainable Future' drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world.
Equal Opportunities: The Free and Hanseatic City of Hamburg promotes equal opportunity. As women are currently underrepresented in this job category at University of Hamburg according to the evaluation, HambGleiG), we encourage women to apply for this position. Equally qualified and suitable female applicants will receive preference. Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.
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