Research Associate “Technical Lead” § 28 Subsection 3 HmbHG

Your responsibilities

Duties primarily include teaching and research. Research associates may also pursue further academic qualifications outside of their work responsibilities.

The Hub of Computing and Data Science (HCDS) is a competence unit for research and forms the core element for the central support of digitalization and digital transformation in research at the University of Hamburg. As Technical Lead, your role encompasses guiding the team of research software engineers from a technical perspective. You ensure sustainable software design, establish architectural patterns, and enable scalability of solutions. Based on extensive experience, you will also drive research projects and support the ongoing development of HCDS.

Specific Duties

• leading the team of research software engineers
• consulting for scientists of all faculties about possibilities, requirements and implementations of data science and general digital solutions for research
• planning, implementation, maintenance, and quality assurance of data science software
• development of all kinds of data-driven systems, all the way from advanced data analytics to multimodal transformer models
• creation of user-friendly interfaces tied to expertise and needs of the users
• analysis and recommendation of state-of-the-art technologies for both models and infrastructure
• DevOps tasks within the scope of application development
• work at the interdisciplinary intersection within the scope of application development and strategic development of (international) cooperation
• teaching 4 hours per week (4 LVS)

Your profile

A university degree in a relevant field, plus doctorate.

• extensive experience in technical multi-project management
• experience in leading large, international teams of researchers in academic workshops, conferences, and shared tasks
• extensive track record of impactful research in the area of NLP, Data Science, and applications of AI in humanities and beyond
• multilingual and multimodal research experience, both for high and low-resource languages
• participation in international committee for research, training, and development
• experience in DevOps, MLOps, and Cloud infrastructure
• showcased research on the state of the art methods in machine learning (esp. transformer models) for multiple years
• excellent programming knowledge in python and other relevant languages
• extensive experience in Data Management and Data Engineering
• expertise and ongoing interest in interdisciplinary research on digitalization challenges
• intermediate German language skills (B1) and fluency in English is required

We offer

• Reliable remuneration based on wage agreements
• Continuing education opportunities
• University pensions
• Attractive location
• Flexible working hours
• Work-life balance opportunities
• Health management, EGYM Wellpass
• Educational leave
• 30 days of vacation per annum

Universität Hamburg—University of Excellence 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 in a digital age” drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work with us in creating sustainable and digital change for a dynamic and pluralist society.

The University of Hamburg is committed to equity. Diversity enriches our university life, whether in our studies, research, teaching, education, or workplace. We therefore welcome all applications, regardless of gender, gender identity, sexual orientation, ethnic or social background, age, religion or belief, disability, or chronic illness.

The University of Hamburg strives to increase the number of women in academia, and encourages qualified female academics to apply.

Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.