Francesco Locatello
10 months ago
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PhD and Postdoc Positions in Causality and Machine Learning at Institute of Science and Technology Austria Institute of Science and Technology Austria in Austria
Degree Level
PhD, Postdoc
Field of study
Computer Science
Funding
PhD positions are fully funded as part of the ISTA PhD program. Postdoc positions are fully funded for two years with a competitive salary (€72,100 gross/year) as part of the FWF Cluster of Excellence on Bilateral AI, with possible extensions and overpayment depending on qualifications. Additional benefits include education and training, cafeteria, childcare, free shuttle bus, health offers, and pension insurance.
Deadline
Expired
Country
Austria
University
Institute of Science and Technology Austria

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About this position
The Institute of Science and Technology Austria (ISTA) is recruiting several PhD students and postdoctoral researchers to join the research group led by Assistant Professor Francesco Locatello. The group focuses on foundational causality and machine learning methods, aiming to advance the understanding of causal representations and models in artificial intelligence. Research topics include learning causal structures from data, developing scalable algorithms, and applying these methods to diverse scientific disciplines such as biology, ecology, and climate science.
PhD positions are open to candidates with a bachelor's or master's degree in natural sciences, mathematics, computer science, physics, chemistry, or related interdisciplinary areas. The program is highly interdisciplinary, offering world-class research facilities, funding and awards, and a vibrant international campus environment. The application portal for the 2026 intake is now open, with a deadline of January 8, 2026. The program starts on September 15, 2026. More details about the curriculum and application process are available on the ISTA graduate school website.
Postdoctoral positions are available for candidates with a PhD in machine learning, statistics, or a relevant field, and a strong publication record in top conferences such as NeurIPS, ICML, ICLR, AISTATS, or CVPR. Successful applicants will lead projects, mentor PhD students, and collaborate within an interdisciplinary network. The postdoc position is fully funded for two years, with a competitive salary of €72,100 gross/year, and is part of the FWF Cluster of Excellence on Bilateral AI. Extensions and overpayment are possible based on qualifications and experience. ISTA offers additional benefits including education and training, cafeteria, childcare, free shuttle bus, health offers, and pension insurance.
Applicants for the PhD program should apply through the ISTA application portal, while postdoc candidates should submit their application documents (cover letter, CV, publication list, and three references) via email to [email protected]. The group encourages individuals from underrepresented groups to apply and is committed to equal employment opportunity. For further information, candidates can consult the research group page, the graduate school homepage, or contact the group leader or postdoctoral office directly.
Keywords: causality, machine learning, artificial intelligence, data science, statistics, biology, ecology, climate science, interdisciplinary research.
Funding details
PhD positions are fully funded as part of the ISTA PhD program. Postdoc positions are fully funded for two years with a competitive salary (€72,100 gross/year) as part of the FWF Cluster of Excellence on Bilateral AI, with possible extensions and overpayment depending on qualifications. Additional benefits include education and training, cafeteria, childcare, free shuttle bus, health offers, and pension insurance.
What's required
For PhD applicants: a bachelor's or master's degree (or equivalent) in natural sciences, mathematics, computer science, physics, chemistry, or related interdisciplinary areas. For postdoc applicants: a PhD in machine learning, statistics, or a relevant area, with a strong publication record in top conferences (NeurIPS, ICML, ICLR, AISTATS, CVPR, etc.), proven ability to conduct independent research, and excellent command of English. All applicants should demonstrate interest in causality and machine learning.
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