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Fully-funded PhD fellowships (m/f/d) for Interdisciplinary Data Science Research
Helmholtz Einstein International Berlin Research School in Data Science (HEIBRiDS)
Interdisciplinary Data Science Research in Berlin – 10 fully-funded PhD fellowships
The Helmholtz Einstein applications for PhD fellowships in a collaborative research environment across disciplinary borders. HEIBRiDS projects combine International Berlin Research School in Data Science (HEIBRiDS) invites Data Science with applications in Molecular Medicine, Materials & Energy, Earth & Environment, Geosciences and Space & Planetary Research and topics belong to the following area:
Machine Learning & Deep Learning
High-throughput Data Analytics
Research will be conducted at one of the partner Helmholtz Centers in the Berlin region:
If you enjoy working in an interdisciplinary environment, producing cutting-edge research, come and join our international community in Berlin, Germany!
Cutting-edge research in data science under close supervision of a team of two mentors
Three-year fully-funded fellowships (E13 TVöD or TV-L), with a possibility of one-year contract extension
Integrated training curriculum of scientific and professional skills courses taught in English
Financial support for conferences and collaborations
To apply, a master‘s degree in quantitative sciences (Computer Science, Physics, Statistics or Mathematics) or related applied field (Bio- or Geoinformatics etc.), awarded by July 2020, is required.
Apply by February 7, 2020, via the online HEIBRiDS application portal. Please submit your CV, academic record, contacts of two referees, and motivation letter referring to the available doctoral project. Detailed description of the available doctoral project can be found hereupon registration to the application portal.
Successful candidates will start their PhD between July and October 2020.
We adhere to principles of responsible research, good scientific practice, openness and transparency, and are committed to setting a good example as a scientific environment where scientists can flourish and grow, independently of their national or ethnic background, functional variation, sex/gender identity/alignment/orientation, family configuration, or other such feature of their persons or contexts.
Severely disabled persons will be given preferential treatment in the case of equal qualification.