The Institute of Science and Technology Austria (ISTA) is offering postdoctoral research positions in the Locatello Group, located near Vienna, Austria. This opportunity is ideal for early-career researchers interested in causal learning, causal representation learning, and the application of machine learning and artificial intelligence to scientific domains such as biology, ecology, and climate science. The Locatello Group focuses on developing theory and algorithms that move beyond pattern recognition to models capable of understanding cause and effect, addressing challenges like interventions, domain shifts, and temporal structure in data. As a postdoctoral researcher, you will develop new theory and algorithms for causal representation learning, work on foundational questions in causality and machine learning, and apply your methods to scientific domains. You will also lead projects, mentor PhD students, and collaborate with a wider network of researchers across ISTA. The position is full-time and based in Klosterneuburg, offering a gross annual salary of approximately €72,100, with potential overpayment depending on experience. The role is fully funded for two years, with the possibility of extension, and is embedded in the FWF Cluster of Excellence on Bilateral AI, providing stable financial support and connections to a broader research network. ISTA is a highly international research institute that combines independent basic research with graduate education, hosting dozens of research groups across mathematics, computer science, life sciences, and physical sciences. The campus environment offers career development training, access to state-of-the-art facilities, childcare support, health initiatives, pension insurance, and a free shuttle bus from Vienna. The Postdoctoral Office and Postdoc Association provide support for administrative questions, relocation, and community building, making ISTA particularly welcoming for international researchers. Eligibility requirements include a completed PhD in machine learning, statistics, or a closely related discipline, a strong publication record in top venues (NeurIPS, ICML, ICLR, AISTATS, CVPR), the ability to conduct independent research, contribute to team projects, and excellent command of English. While interdisciplinary experience is not required, a genuine interest in applying AI to scientific problems is essential. Applicants should also be able to mentor students and collaborate within a research group. To apply, candidates should carefully read the official job posting for the Locatello Group postdoc, prepare a cover letter, CV, publication list, and contact details for three references, and submit their application by email directly to the group leader at [email protected], mentioning possible starting dates and outlining project ideas. Additional opportunities can be explored via the ISTA jobs portal and fellowship programs. This postdoctoral position offers a well-funded, interdisciplinary environment with strong support structures, competitive salary, and a clear expectation of scientific excellence. It is an excellent next step for researchers whose work engages with causality, robustness, or model interpretability, and who wish to accelerate their academic or research career in a collaborative and innovative setting.

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.