HEIBRiDS PhD Fellowships in Data Science
More details :
The HEIBRiDS PhD Fellowships are funded doctoral positions in Germany for applicants interested in data science and its applications in major research fields. The programme combines advanced data science methods with real scientific challenges in areas such as molecular medicine, materials and energy, earth and environment, and geosciences.
Research is carried out at partner Helmholtz centres in the greater Berlin area, including GFZ, Helmholtz Zentrum Berlin, and the Max Delbrück Center, in collaboration with partners such as BIFOLD, Charité, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Technische Universität Berlin.
At Darrab Education, we recommend this opportunity for strong students with backgrounds in computer science, mathematics, physics, statistics, bioinformatics, geoinformatics, data science, AI, or related fields. It is a strong opportunity, but applicants should always check the official HEIBRiDS website before applying because deadlines, projects, and requirements may change.
Eligibility :
Hold, or expect to obtain, a university degree equivalent to a Master’s degree.
The degree should include a written research thesis.
Eligible backgrounds include:
Computer science
Physics
Statistics
Mathematics
Bioinformatics
Geoinformatics
Related fields
Applicants still studying may apply if they expect to receive their degree within the required period after the interview stage.
Master’s-equivalent degrees may include MD, MRes, MTech, integrated programmes, BSc-MSc programmes, or BTech-MTech dual degrees.
Applicants must have relevant research experience, such as Bachelor’s or Master’s research projects, lab rotations, study exchange, internships, or other research projects.
A research Master’s thesis is normally required, but exceptions may apply for some programmes such as MD or pharmacy-related tracks.
Required final Master’s grade is generally 75% or higher, or a German grade of at least good, meaning better than 2.5.
Applicants must be early-stage researchers and should be within the first four years of their research career.
Applicants must not already hold a doctoral degree.
Good written and spoken English is required.
German language skills are not required.
English tests such as TOEFL, IELTS, or Cambridge CAE are recommended for non-native speakers, but they are not mandatory for the application.
Required documents :
Short CV, maximum 2 pages.
Transcript of the highest degree awarded, including courses and grades.
Certificate of the highest degree awarded.
Temporary transcript with grades if the Master’s degree is not yet completed.
Certified English or German translation if documents are not issued in English or German.
Two reference letters submitted directly by referees through the application system.
Research and motivation statements inside the online application form.
Optional short video answering the question requested in the application portal.
Optional GRE score.
Optional English proficiency test.
How to apply :
Visit the official HEIBRiDS Open PhD Positions page.
Register through the online HEIBRiDS application portal.
After registration, check the available projects and participating research groups inside the portal.
Choose the labs and projects that best match your research interests.
Complete the application form in English.
Add details about your academic background, research experience, research interests, motivation, and project preferences.
Enter the contact details of two referees.
Make sure your referees submit their recommendation letters before the deadline.
Upload all required documents in PDF format.
Submit the application through the online portal before the deadline.
Applications by email or through other job portals are not accepted.
The Scholarship Benefits:
Funded PhD fellowship for 4 years.
Doctoral research in Berlin and the greater Berlin area.
Work with leading Helmholtz centres and Berlin universities.
Interdisciplinary research environment combining data science and scientific applications.
Training in modern data science methods, including AI, machine learning, explainable AI, modelling, and imaging data science.
International research community.
English-speaking programme environment.
Opportunity to work on projects connected to real-world scientific challenges in health, energy, environment, materials, and geosciences.