The programme combines advanced study, scholarly discussion, and dissertation work, enabling doctoral candidates to build competence in algorithmic design, data-driven investigation, experimental evaluation, and the development of digital applications. Candidates engage with both conceptual foundations and practical implementation, exploring the broader scientific, technological, and societal dimensions of the discipline while preparing a monograph or article-based dissertation for public defence. Programme Structure Courses include: Natural Language Processing Computational Linguistics Computational Semantics Computational Syntax NLP Theory and Method Statistical Modelling Machine Learning Admission requirements Academic requirements We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme. English requirements TOEFL iBT: 90 PTE Academic: 62 IELTS: 6.5 General requirements Second-cycle qualification, or at least 240 credits including 60 credits at second-cycle level, or equivalent knowledge. Sufficient English proficiency to participate in courses, seminars, and related activities. In addition, one of the following must be met: At least 30 second-cycle credits in Computational Linguistics, Language Technology, or Natural Language Processing, including a thesis of at least 15 credits. At least 30 second-cycle credits in Linguistics or Cognitive Science, including a thesis of at least 15 credits, plus at least 30 credits in Computational Linguistics, Language Technology, Natural Language Processing, Computer Science, Logic, or Mathematics. At least 30 second-cycle credits in Computer Science, Logic, or Mathematics, including a thesis of at least 15 credits, plus at least 30 credits in Linguistics, Cognitive Science, Computational Linguistics, Language Technology, or Natural Language Processing. Tuition Fees PhD students do not pay tuition fees. Duration Full-time: 48 months

The programme combines advanced study, scholarly discussion, and dissertation work, enabling doctoral candidates to build competence in algorithmic design, data-driven investigation, experimental evaluation, and the development of digital applications. Candidates engage with both conceptual foundations and practical implementation, exploring the broader scientific, technological, and societal dimensions of the discipline while preparing a monograph or article-based dissertation for public defence. Programme Structure Courses include: Natural Language Processing Computational Linguistics Computational Semantics Computational Syntax NLP Theory and Method Statistical Modelling Machine Learning Admission requirements Academic requirements We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme. English requirements TOEFL iBT: 90 PTE Academic: 62 IELTS: 6.5 General requirements Second-cycle qualification, or at least 240 credits including 60 credits at second-cycle level, or equivalent knowledge. Sufficient English proficiency to participate in courses, seminars, and related activities. In addition, one of the following must be met: At least 30 second-cycle credits in Computational Linguistics, Language Technology, or Natural Language Processing, including a thesis of at least 15 credits. At least 30 second-cycle credits in Linguistics or Cognitive Science, including a thesis of at least 15 credits, plus at least 30 credits in Computational Linguistics, Language Technology, Natural Language Processing, Computer Science, Logic, or Mathematics. At least 30 second-cycle credits in Computer Science, Logic, or Mathematics, including a thesis of at least 15 credits, plus at least 30 credits in Linguistics, Cognitive Science, Computational Linguistics, Language Technology, or Natural Language Processing. Tuition Fees PhD students do not pay tuition fees. Duration Full-time: 48 months