CIDAS-Fellowship 2023The Campus Institute Data Science (CIDAS) is a central scientific unit of the Georg-August-Uni- versity Göttingen. CIDAS promotes interdisciplinary exchange and activities among faculties and campus-wide in the field of data science. The CIDAS invites applications for two fellowships for outstanding young scientists to pursue their own innovative research agenda in the field of Data Science and Artificial Intelligence.
CIDAS supports young scientists at an early stage of their career to independently develop projects and to create a perspective to work independently for several years at the Göttingen Campus in the field of Data Science. In particular, the collaboration between methodological or theoretical researchers and applied scientists at the Göttingen Campus and within CIDAS should be promoted. The application should describe the career perspectives of the applicant and show how it opens a path to scientific independence and own third-party funding.
Who can apply:
Outstanding young scientists who are in the final phase of their PhD (last year) or early postdoc phase (maximum 2 years after completing the PhD) with an idea for their own research project in the field of Data Science. This can be in the fundamentals of Data Science, applied Data Sci- ence, or in the social science aspects of Data Science. The project should be a collaboration with at least one member of CIDAS. Other collaborations with groups outside CIDAS are also possible and encouraged. If the applicant is not already a CIDAS member, they will become members upon approval of the application. The position can be used in particular for prepara- tory work for a subsequent application for a research grant or an independent research group.
Scope of funding:
The funding of the Fellowship includes up to €75,000 each, which can be used, for example, to fund the applicant's own position (Decision subject to personnel law possibilities).
Documents to be submitted:
• Description of the research idea (max. 5 pages), incl.:
- Clearly defined content-related goals, comprehensible time and cost schedule
- Possible perspectives after the project, career perspectives, possibly plan for external funding
- Planned collaboration with CIDAS members and other scientists
- Innovation of the application
• Curriculum vitae
• Letter of recommendation from the supervisor or mentor, including a workplace (incl. infrastructure) commitment for the period to be funded. The mentor should not have previously served as the applicant’s PhD supervisor.
Deadline: Sunday, November 13th, 2022
Application by e-mail to: email@example.com
The applications received will be thoroughly reviewed and decided upon by the CIDAS Board and its representatives immediately after the deadline. At the time of application, CIDAS membership is not required. Membership in CIDAS is only required when approved funds are used. The funds are to be spent immediately after approval. The funds will be allocated by CIDAS or the University of Göttingen.
If you have any questions, please don't hesitate to contact the CIDAS management: Dr. Isabelle Matthias (firstname.lastname@example.org)
Dr. Helena Bestová
Project: Natural language processing and automated trait-mining workflows for studying plant size distributions on islands
Prof. Dr. Constantin Pape
Project: Image segmentation with minimal supervision for live-cell imaging
Project: Finding the tipping point in dilated cardiomyopathies: A dynamical systems' analysis of single cardiomyocytes functional and morphological long-term trajectories using big data
Dr. Fatemeh Ziaeetabar
Department for Computational Neuroscience
Bernstein Center for Computational Neuroscience
III Physikalisches Institut-Biophysik
Friedrich-Hund Platz 1 37077, Göttingen Germany
Tel: +49 (0) 15253766570
E-mail: fziaeetabar [at] gwdg.de
Project: Construction of a system to describe the actions of several actors and exemplary application for the semantically-layered annotation of video image sequences
Data Fusion Group
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Goldschmidtstr. 7, 37077 Göttingen
Tel: +49 (0) 551 39 172030
Email: shishan.yang [at] cs.uni-goettingen.de
Project: Efficient Tracking based on Probabilistic Registration of Automotive Radar Data
Statistics and Econometrics
Humboldtallee 3, 37073 Göttingen
Tel: +49 (0) 551 39 24605
Email: anne.berner [at] uni-goettingen.de
Project: Trade-off or synergy? Energy-related emissions and digitalization in the manufacturing industry