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Professorship (W3) for Informatics with a Focus on Data Science

Employer
Universität Hamburg
Location
Hamburg (DE), Germany
Salary
Negotiable
Closing date
May 25, 2024

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Professorship (W3) for Informatics with a Focus on Data Science

Institution:Faculty of Mathematics, Informatics and Natural Sciences
Commencement of duties:Summer Semester 2025
Application deadline:2024-06-06

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" 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.

Universität Hamburg offers data-intensive fields of application and various research opportunities in informatics through its core research areas Climate, Earth and Environment; Infection Research; Particle, Astro- and Mathematical Physics; Manuscript Cultures; and Neurosciences and Cognitive Systems. These interdisciplinary possibilities and broad-based core informatics make Hamburg the ideal location for research in informatics, artificial intelligence, and data science methods. Whether you are a researcher at the beginning of your career or an established expert, work with us to shape the excellent strategic development of Hamburg into an international data hub for informatics.

Responsibilities

The Faculty of Mathematics, Informatics and Natural Sciences is seeking a professor (W3) of informatics with a focus on data science.

The successful candidate is expected to develop the fundamental statistical and computer-based methods for creating, processing, and analyzing complex and large amounts of data. Proven knowledge and experience in data analysis, machine learning, artificial intelligence, as well as handling and processing large amounts of data is required.

The professor is expected to participate in the University's core research areas .

Potential method-oriented research areas include those in the fields of computational stochastics and statistics, analytics of visual and multimodal data, distributed learning from data, and aspects of reliability for data analysis. The professorship should also strengthen core informatics in research and teaching through a basic focus on the informatics aspects of data science.

In collaboration with the W3 professorship for data engineering, the successful candidate is expected to further develop the data science activities in the Department of Informatics and improve cooperation with other Hamburg universities and nonuniversity research institutions in the field. The professorship is expected to link with the department's research activities in the field of cognitive systems. In addition, involvement in the University's activities in the House of Computing and Data Science (HCDS) is also desired.

The professor is expected to actively participate in the degree programs of the department and be available for teaching in other degree programs. In particular, participation in the newly established English-language Master of Science in Data Science and Artificial Intelligence is expected.

Your profile

We are looking for a candidate with an outstanding academic track record and research experience in the professorship field.

In addition to international recognition, applicants are expected to have an excellent track record of publications and projects attesting to outstanding research in the field outlined, and at least one of the method-oriented research foci. Applicants should also demonstrate the willingness and ability to collaborate in the department's and the faculty's research areas as well as outside of these institutions, for example in application-related cooperation projects.

The successful candidate is required to have experience and a successful track record in acquiring third-party funding for projects. In addition, very good didactic skills and experience in university teaching are expected. Experience with managing staff is desirable.

In addition, German-language proficiency or the willingness to obtain these skills within two years of commencing is desired.

Additional information

Universität Hamburg values gender equality, diversity, and finding a balance between family life and working or studying. Integrating these values into teaching and management is expected. We also expressly encourage qualified women to apply.

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

Instructions for applying

Contact

Prof. Dr. Timo Gerkmann
timo.gerkmann@uni-hamburg.de
+49 40 42883-2438 Prof. Dr. Sören Laue
soeren.laue@uni-hamburg.de
+49 40 42883-2443

Reference number
2433/W3

Application deadline
2024-06-06

Upload all supporting documents as a single PDF:

  • cover letter
  • CV
  • list of publications
  • proof of teaching experience
  • proof of experience and success in acquiring external funding and conducting externally funded projects
  • certificates and supporting documents
  • 3 representative publications
  • course list
  • statement outlining your plans for future research and teaching
  • evaluations, if applicable
  • further supporting documents such as talks, posters, important positions within organizations, if applicable

If you experience technical problems, send an email to bewerbungen@uni-hamburg.de .

Further information on the academic search procedure and the assessment center process is available www.uni-hamburg.de/appointment-procedure .

Read more information on data protection in selection procedures .

Section 15 Hamburg higher education act (Hamburgisches Hochschulgesetz, HmbHG) applies. The nature and scope of tasks are determined pursuant to Section 12 subsection 7 HmbHG.

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