Recruitment Process

My recruitment for PhD students is primarily focused around the annual Mila application process, which typically takes place around December for students starting in September of the following year.

When I am actively recruiting, I will advertise positions clearly here on my website and on my LinkedIn profile. It is rare for me to recruit outside of this timeline.

Of course, truly exceptional and highly motivated students whose research interests perfectly align with my work are always welcome to send a spontaneous application. However, due to the volume of emails I receive, I cannot guarantee a reply.

Research Opportunities

Students and postdocs interested in the following themes are welcome to apply:

• Linguistic and computational evaluation of large language models
• NLP for low-resource languages
• Machine translation of domain-specific texts
• Cultural and linguistic bias in AI systems
• Multilingual knowledge representation in neural models

Note: Some themes reflect established expertise (computational terminology, LLM evaluation). Others represent interests I am expanding (NLP for very low-resource languages). Co-supervision ensures students receive diverse complementary expertise.

What I Look For

• Background: Strong foundation in computational linguistics, NLP, linguistics, or translation studies
• Technical skills: Programming experience (Python preferred), familiarity with machine learning concepts (or motivated to learn)
• Language skills: Proficiency in English and French; additional languages are an asset
• Research mindset: Curiosity, critical thinking, and enthusiasm for interdisciplinary research
• Research focus: Genuine interest in language as a central component of your research; If you're primarily interested in hardcore machine learning or the most technical aspects of AI without a language focus, I may not be the right supervisor for you

Before You Apply: Important Information

About my supervision approach:

• I am an applied linguist with computational expertise. My research requires strong interdisciplinary skills.
• I actively seek co-supervisors with complementary expertise to ensure diverse perspectives and broader networks.
• All students must be based in Montréal (no remote supervision).

About applications:

• I can only respond to applications that clearly align with my research. Review my work carefully and explain the connection.
• Generic applications will not receive a response.

About funding:

• I only accept PhD students I can fund. All accepted students have full financial support (you need not secure funding before applying).
• Students are expected to apply for external funding (with my support) to supplement stipends and enhance CVs.
• I do not currently fund MA thesis supervision. Task-specific RA positions are occasionally posted through UdeM networks.

Application Process & Timeline

For PhD applicants:

My main recruitment path is the annual Mila application process (link). This process typically opens in mid-October with a deadline in early December for admission the following September.

Mila acceptance leads to one of three UdeM programmes (with almost guaranteed admission):

• Doctoral programme in Linguistics: Starting date September; French level B2 required
• Doctoral programme in Translation: Starting date September; French level B2 required
• Doctoral programme in Computer Science: Starting date September or January; no French required (though encouraged)

All students are affiliated with both Mila and UdeM.

Postdocs and visiting scholars can apply by email:

• CV
• Brief personal statement on research interests and proposed collaboration
• References (if available)

Past Students

PhD

Victor De Marez (2023-2024, co-supervised with Prof. Dr Tim Van de Cruys)
Topic: Bilingual lexicon induction as a probing task to explore cross-lingual lexico-semantic knowledge in language models
Note: Due to my emigration to Montréal, I had to discontinue my supervision. Victor is continuing his PhD at the University of Antwerp under supervision of Prof. Dr Walter Daelemans.

MA Theses

• Rune Devreker (2024): Evaluation of EN-NL translation quality of ChatGPT vs DeepL for legal texts
• Jakob Michiels (2023, research internship): Linguistic information for sequential automatic term extraction
• Gilles Floréal (2021, co-supervised): Automatic term extraction
• Anneleen Dill (2021, research internship): Multilingual automatic term extraction from comparable corpora
• Kim Steyaert (2019, research internship): Monolingual term extraction features to link cross-lingual equivalents

BA Papers

• Noémie Joos (2024): Comparison and evaluation of translation capabilities of ChatGPT vs DeepL
• Laura Tuytschaever (2019): Automatic term extraction with supervised machine learning
• Yesim Dumont (2018): On the nature of terms and term annotation
• Maxime Van Belle (2018): Quantitative research of automatic term extraction