Iryna Gurevych
6 months ago
AI and Machine Learning University of Vienna, Technical University Darmstadt in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Both positions are fully funded PhD opportunities, covering tuition and providing a stipend. Specific stipend amounts are not mentioned, but funding is described as 'fully funded.'
Deadline
Jun 24, 2026
Country
United Kingdom
University
Universität Wien

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About this position
Funding details
Both positions are fully funded PhD opportunities, covering tuition and providing a stipend. Specific stipend amounts are not mentioned, but funding is described as 'fully funded.'
What's required
Applicants should have a strong academic background in computer science, artificial intelligence, machine learning, or related fields. Experience or interest in NLP, explainability, or AI safety is highly desirable. Candidates must meet the entry requirements of the respective university, which typically include a relevant master's degree or equivalent, strong programming and analytical skills, and proficiency in English. Additional documents such as motivation letter, CV, transcripts, recommendation letters, and publications may be required.
How to apply
Apply online via the provided university application links. Prepare and submit all required documents, including motivation letter, CV, transcripts, and recommendation letters. For TU Darmstadt, recommendation letters can be sent directly to Prof. Dr. Iryna Gurevych. Ensure your application is complete before the deadline.
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If you’re passionate about Machine Learning, Natural Language Processing (NLP), and AI Safety, here are two outstanding fully funded PhD positions currently open at top institutions:
University of Vienna – Austria
Location: Vienna
Focus: Explainability for Machine Learning & NLP
Deadline: 24th June 2025
Apply here: https://lnkd.in/ei-tF4MB
Technical University Darmstadt – Germany
Location: Germany
Focus: AI Safety, NLP, and ML
Deadline: 29th June 2025
Apply here: https://lnkd.in/ei8xeq3j
These positions are ideal for researchers aiming to work at the intersection of cutting-edge AI and societal impact, in supportive, research-intensive environments.
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