We have positions of Student Researchers, PhD openings, postdocs, and interns. We are open for consultations to all entities. [Update: All forms have been last checked on 20 Mar 2025, and suitable candidates have been contacted.]
Apply to be a Student Researcher with Us
We welcome students who can devote 6 months to 2 years of time working with us. You can be of any career stage, from anywhere on the earth.
Category 1: For ETH Master students, I’m very interested in hosting Master Thesis, Semester Projects, and general research collaboration. On MyStudies, we can host you under Prof Bernhard Schoelkopf or Prof Mrinmaya Sachan. In special cases, strong ETH undergrads can apply too.
Category 2: For UToronto students, I can host students based on their backgrounds in the application form. Students with previous research experiences and/or strong coding or math background is highly welcome.
Category 3: For students from anywhere on earth with any background (e.g., master/undergrad/gap-year student, and people who want to do research in their spare time regardless of the day job), check out the skill preferences in my form and welcome to apply.
*Students with a diversity background can also try reaching out to PhDs/postdocs of Prof Rada Mihalcea at UMich to see if they have capacities to host projects.
Examples of our students and their achievements:
- ETH Master students
- Giorgio Piatti
- Flavio Schneider
- UToronto students
- Punya Syon Pandey
- UMich students
- Jiarui Liu
- Remote students
- Ojasv Kamal
By default, most research opportunities are remote, unless you are in the same city as me.
Internships: In very selected cases, we may be able to host in-person internships at Max Planck Institute in Tuebingen Germany, and Vector Institute Internship programs.
PhD Applications
I look for several PhDs for my Jinesis Lab at UofT Computer Science. In the PhD admission at UofT, individual professors have a large decision power.
Channel 1: PhD at the University of Toronto
If you want to apply for a PhD with me in the foreseeable future (i.e., usually >=1 year from now) via the UToronto CS PhD application, it will be an advantage if you have already worked with me. Check out the pre-PhD research form.
For the ongoing admission, I’m hesitating over the last offer, for which potential candidates are contacted. Last notification batch=Apr 25-May 15.
Channel 2: PhD via the ELLIS PhD program
As a CIFAR AI Chair, I am listed as an advisor in the ELLIS PhD program too. You can either directly apply to me as your ELLIS main supervisor, or contact me to be a co-supervisor if you are already admitted by a main supervisor. Me and Bernhard Schoelkopf can co-supervise quite several students together, so you are recommended to tag both of us. Check out the ELLIS PhD application by Nov 15.
Channel 3: PhD at Max Planck Institute with Prof Bernhard Schoelkopf, and co-supervised by me
I will co-supervise students together with Prof Bernhard Schoelkopf, so you can directly apply to him and cc’/tag me mentioning that you are interested in co-supervision. Here are some channels to apply, such as the ELLIS PhD program, and IMPRS application to the Max Planck Institute for Intelligent Systems.
Postdocs
People interested in a postdoc with me can check out these fellowship opportunities to fund your stay at UToronto, and then you can see if our research direction matches via emails to me with the subject “[Postdoc interest match] XXX”.
Consultation
If you are a company, an organization, or a government sector, please email me to book consultation hours. Any for-profit organizations need to pay for the consultation by 30-min per slot.
Our Collaborators
Our diverse collaborators caters to a wide range of projects on AI, ranging from theoretical AI improvements to interdisciplinary applications in downstream use cases.
Prof Bernhard Schoelkopf
Director, Max Planck Institute
Prof Mrinmaya Sachan
Assistant Professor, ETH Zürich
Prof Rada Mihalcea
Head of AI, Professor, UMich
Prof Mona Diab
Professor, Head of CMU LTI
FAQs
What type of students do I look for as PhDs?
Ideally I hope my lab to have students of (any of the following) diverse expertise: (1) experienced with ACL/NeurIPS-type publications, (2) very strong in coding, (3) deep philosophical thoughts (with a background in phil/math/physics/etc) and interested in the philosophy of science, and (4) a student with expertise in math/stats who is either already fluent in or can quickly learn formal causal inference. Above all, I hope that all my students are kind and supportive of each other.
Case studies of PhD applicant examples whom I will like very much if they apply to me:
- Student A is from a country/environment with less NLP resources, but they showed their strong research skills by having 2+ first-author publications at *ACL or NeurIPS. Student A also has a great character to help other people, with experience mentoring more juniors students, and organizing events. Examples: Jiarui Liu and Andrei Muresanu
- Student B is very good at causal inference. Example: Sean Richardson
- Student C has extensive past project experiences with researchers in my trusted network, on topics I care about. Their corresponding mentor(s) also sent a very positive strong recommendation message to me. Examples: Amir Zur, and Carrie Yuan
- Student D is very good at the {history of science, or understanding of political systems across several countries} which can usually reflected by that we can chat for very long without feeling tired. I have a line of research that turns such insights into socially impactful computational projects. Examples: David Guzman (University of Zürich)
- Student E does not have many research publications, but has a track record to learn anything fast and smartly. Ideally this quality has been demonstrated in our Pre-PhD project together. Example: Samuel Simko
- Student F shows extraordinary strength in something: e.g., as a software engineer, managing many open-source codebases; a fun NLP+X domain; etc.
Every student is unique. I welcome you to introduce yourself to me as much as possible through the designed questions in my Google form. You could be accepted by unique reasons — congrats! However, if you got declined, then you can always seek inspirations from the above case studies.
Why Pre-PhD research with me before you apply?
The main reason why I suggested pre-PhD research with me is that I can have a better prediction of how life will be with you as my PhD for four or five years. It especially applies to students who are from a diverse set of backgrounds, as part of my fairness pursuit in recruiting.
For PhD admission later, everything is about what reliable and strong signals I can get when predicting the future many years with you. Such signals can be from your papers and recommendation letters when you apply, and can also be from direct interaction with you through a project.
Visa Issues and Collaboration Constraints
Since AI is listed as a sensitive technology, nowadays we have to conform with certain policies and regulations. If you are an individual from Iran, Russia, or China, (1) for remote student collaboration, I am not allowed to collaborate with anyone from the list of sensitive institutions; (2) for any channel that requires a Canadian student visa for you, please be aware of reported cases of student visa delay, especially from sensitive institutions; (2) for any channel that leads to a student visa in Germany, please check ASPI university tracker to see whether your institution will trigger a strong security check for a German visa.
What if your application does not work out with me?
There are many fantastic opportunities out there as well! If you have general career planning questions, you are very welcome to join our ACL Year-Round Mentorship, for Zoom sessions and slack. Additionally, feel free to check out the research opportunities with other NLP and/or AI Safety researchers.
To second-time applicants:
If you or applying to me the second time or more, then the most important thing is to highlight your “growth / change” between your recent two applications. For example, you should have an annotated CV contrasting the difference of your old version and the new version (similar to a journal article revision). You can also write a google doc of any skill or experience differences when filling out corresponding answers in the application form. Regardless of whether you get it this time or not, I want to say kudos for your growth!
In case it is helpful, here are some other research opportunities:
Use Our LLM Causal Agents
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