The European Laboratory for Learning and Intelligent Systems (ELLIS) has opened applications for its 2026 PhD recruitment round, offering outstanding candidates opportunities to pursue doctoral research in artificial intelligence (AI), machine learning, and related interdisciplinary fields across Europe. Successful applicants will join an international research network connecting leading academic institutions, industrial research partners, and experts working at the forefront of intelligent systems. The programme is designed to develop the next generation of AI researchers through collaborative supervision, international research exchanges, specialised training, and networking opportunities. Its 2026 application round is recruiting students for PhD programmes beginning in 2027, with research placements dependent on the selected advisor and institution. Application deadline: 31 October 2026, at 23:59 Anywhere on Earth (AoE). Programme start: 2027, depending on the advisor and host institution. Location: Participating institutions across Europe, with selected international collaborations. About the ELLIS PhD Program ELLIS is a European research initiative focused on advancing excellence in machine learning and intelligent systems. Its PhD programme connects promising doctoral candidates with established researchers through structured international collaborations. Each candidate is jointly supervised by researchers based in different institutions or countries, encouraging cross-border knowledge exchange and collaboration. Students also participate in training activities, workshops, summer schools, and research networking events. The programme receives support from European Union-funded initiatives, including ELIAS and ELLIOT. G-Research also supports the ELLIS PhD and Postdoc Program through scholarship funding through 2028. The programme is highly competitive. ELLIS reports that fewer than 5% of registered applicants and approximately 5–10% of eligible applicants are typically accepted. Available Research Areas Candidates can explore a wide range of machine learning-driven research fields, including: Deep learning, machine learning theory, and algorithms. Computer vision, natural language processing, and robotics. Bayesian learning, causal inference, and reinforcement learning. AI safety, security, interpretability, fairness, and trustworthy machine learning. Bioinformatics, computational neuroscience, and health. Earth and climate sciences, sustainability, and environmental applications. Human-computer interaction, human behaviour, and psychology. Machine learning applications in finance, chemistry, physics, and engineering. Law, ethics, privacy, social sciences, and humanities. Applicants can indicate their preferred research areas and potential supervisors from the advisors participating in the current recruitment round. Three PhD Research Tracks 1. Academic Track This track supports collaboration between academic researchers in different European countries. Candidates work with two eligible ELLIS researchers and must spend at least six months visiting their secondary advisor in another European country. The visit can be divided into separate periods. An exception may allow a co-supervisor outside Europe if that researcher is an ELLIS Fellow or Scholar. 2. Industry Track This track connects doctoral researchers with academic and industrial research partners. Candidates must spend at least 50% of their time at the academic partner institution and a minimum of six months with the industry partner. The industry placement may be continuous or distributed over time. The industry partner, research laboratory, and industry advisor must be based in Europe. 3. Interdisciplinary Track This option supports research combining AI or machine learning with another discipline, such as biology, law, finance, or the social sciences. Candidates work with an ELLIS researcher and a tenured academic in a field unrelated to AI or machine learning. Students must spend at least 50% of their time with their primary advisor and at least six months with their secondary advisor, subject to the programme’s specified exceptions. The doctoral degree must generally be awarded by a European institution, except where an eligible CIFAR Fellow or Canadian AI Chair holder participates in the supervision arrangement. Eligibility and Supervision Requirements Applicants should demonstrate strong academic preparation, research potential, and an interest in contributing to machine learning or related fields. Specific admission requirements depend on the participating advisor and institution. The application portal lists eligible advisors who are recruiting during the current round. Applicants should prioritise finding a suitable primary advisor, while the co-advisor can generally be selected later, within five months of acceptance. Some institutions require a separate application through their own admissions systems. Candidates should check each advisor’s profile and submit any required parallel institutional applications before the relevant university deadlines. Required Application Documents Applicants must register on the ELLIS application portal and complete all required sections by the deadline. The application includes: Application form: Personal information, educational qualifications, relevant experience, research interests, and preferred advisors. Two-page motivational letter: An explanation of the applicant’s interest in the ELLIS network, previous research projects, research interests, and future research direction. Curriculum vitae: Academic background, employment history, publications, presentations, awards, and relevant research experience. University transcripts: Unofficial transcripts for undergraduate and master’s studies, accompanied by English translations where necessary. Optional supporting material: A thesis, published paper, or research portfolio combined into a single PDF under 20 MB. References: Contact details for at least two and no more than three referees. At least two referees should hold established professional positions, such as independent investigator, principal scientist, group leader, or lecturer. No more than one reference may come from a postdoctoral researcher. References from PhD students and classmates are not accepted. Applicants must request references through the portal before the application deadline. Referees have until 25 November 2026, at 23:59 AoE, to submit their recommendations. Applications missing the required references after this deadline will be considered incomplete. Important Application Dates 1 October 2026: Application portal opens. 31 October 2026: Final deadline for applications and reference requests, at 23:59 AoE. November–December 2026: Application review. January–February 2027: Interviews. Late February–March 2027: Admission decisions. 2027: Programme commencement, depending on the host institution and advisor. How to Strengthen an Application Candidates should prepare a focused research statement, identify advisors whose expertise closely matches their interests, and clearly explain the potential contribution of their proposed research. A strong CV should highlight relevant research experience, technical skills, publications, and evidence of independent problem-solving. Applicants should approach referees early and verify whether their preferred institutions require parallel applications. Because the programme is highly competitive, incomplete submissions or missed institutional deadlines may jeopardise an application. ELLIS explicitly encourages applications from women and people living with disabilities, supporting broader representation in AI research. How to Apply Interested candidates should register and submit their applications through the official ELLIS PhD and Postdoc portal. VISIT OFFICIAL WEBSITE TO APPLY For enquiries, contact the ELLIS PhD Coordination Office at phd@ellis.eu. For more opportunities such as these please follow us on Facebook, Instagram, Twitter, LinkedIn and WPChannel Disclaimer: Global South Opportunities (GSO) does not take ownership or credit for the opportunities shared on this platform. All opportunities are sourced from official announcements and external sources for informational purposes only. Applicants are encouraged to verify all details, deadlines, and eligibility requirements from the official source before applying. 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