Join InfoLab
Fully funded M.S./Ph.D. Combined and Ph.D. research positions at the Information Research Laboratory, Sungkyunkwan University (SKKU), led by Prof. Tamer Abuhmed. We work on AI security and adversarial machine learning, trustworthy and explainable AI, and biomedical AI. Build rigorous research, publish at strong international venues, and grow into an independent researcher.
Currently Open Graduate Programs
M.S./Ph.D. Combined Fully Funded
An integrated route from master's coursework through to the doctorate, without a separate re-application between degrees. Best suited to candidates who already intend to complete a Ph.D. and want to begin research early.
Ph.D. Fully Funded
For candidates who already hold a master's degree, or equivalent demonstrated research experience, and are ready to take ownership of a research direction and drive it to publication.
Standalone M.S. positions are not available at this time. We are currently recruiting only for the M.S./Ph.D. Combined and Ph.D. programs. If you are seeking a master's-only degree, this call is not the right fit — but you may still be a strong candidate for a research internship.
Fully Funded Graduate Research
Graduate researchers admitted to the programs above are funded. You should be able to focus on research rather than on financing your degree.
- Full tuition fee waiver — 100% of tuition is covered for the duration of your funded position.
- Monthly stipend — ongoing financial support so that research is your primary work.
- Research computing resources — access to the lab's computing infrastructure for training and large-scale experimentation.
- Direct mentorship from the PI and senior researchers, with regular technical feedback on your work.
- Publication-oriented training — you will be supported in working toward first-author papers at strong international venues.
- Active research projects — funded, ongoing work with real problems rather than invented exercises.
- Collaboration with academic and industrial partners in Korea and internationally.
- Conference participation support, subject to project funding and the stage of your work.
Research Areas
Read these before applying. The strongest applications name the specific problems the candidate wants to work on.
AI Security & Adversarial ML
Adversarial attacks and defenses, robustness of deep learning and foundation models, attacks against interpretable systems, robust malware detection, federated learning under poisoning, and behavioral biometric authentication.
Trustworthy & Explainable AI
Explainability and interpretability, uncertainty and reliability, robustness and fairness as joint objectives, and dynamic ensemble methods for dependable decision-making. This theme runs through most of what we do rather than sitting beside it.
Biomedical & Healthcare AI
Trustworthy clinical AI, multimodal medical data, disease progression modelling, medical imaging, clinical prediction such as ICU outcomes, and large language models for clinical decision support.
See all research projects and our 114 publications to judge research fit for yourself.
Why InfoLab
- Publication-oriented culture. Recent work has appeared at venues including NDSS, ACM SIGKDD, EMNLP Findings, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Dependable and Secure Computing, and Information Fusion.
- Focused mentorship. A lab deliberately sized so that supervision is direct and individual, not delegated down a long chain.
- Interdisciplinary by design. Security, machine learning, and clinical problems sit in the same group, so methods developed for one area are tested against the others.
- A genuinely international group. Our researchers come from many countries — see the current team. Research and publication are conducted in English.
- Development toward independence. The aim is not that you execute assigned tasks well, but that you leave able to define and defend your own research agenda.
- SKKU and the Korean technology ecosystem. A research university with strong engineering infrastructure, situated in one of the world's most active technology economies.
Who We Are Looking For
We are looking for researchers with the preparation and persistence to do original work. Strong candidates typically show several of the following:
- Research potential — evidenced by prior academic research, a thesis, a research assistantship, publications or preprints, or substantial industrial R&D.
- Solid foundations in mathematics and machine learning — linear algebra, probability, optimization, and the ability to reason about why a method works.
- Real implementation ability — Python and a deep-learning framework such as PyTorch; systems or security tooling for security topics.
- The ability to read papers independently and reconstruct what a method actually does, including its weaknesses.
- Evidence you finish things — a completed thesis, a shipped system, a reproducible open-source project, or a paper carried through to submission.
- Clear written communication. Research is reading, writing, and arguing from evidence at least as much as it is coding.
- Independence with collaboration — able to drive your own work forward while contributing to a shared research group.
- Genuine alignment with the research areas above, rather than a general interest in AI.
You are not expected to satisfy every item on this list. We evaluate research potential, preparation, and fit holistically. Candidates arrive from different starting points, and an applicant who is exceptionally strong in one dimension is more interesting to us than one who is uniformly average across all of them.
Two Paths to Joining as a Graduate Researcher
There are two ways into the lab. Neither is superior — they suit different candidates. An InfoLab internship is preferred in some cases, but it is not mandatory.
Path A — Research Internship Preferred, not required
Join us first as a research intern, then apply to the graduate program. This path suits you if you have limited formal research experience, want to demonstrate your potential through actual work, or would rather understand our research environment before committing to several years of study.
The internship works as a mutual research-fit evaluation: you see how we work, and we see how you think. Many strong candidates choose this route deliberately, even when they could apply directly.
Path B — Direct Application No internship needed
Apply directly to the M.S./Ph.D. Combined or Ph.D. program without an InfoLab internship. This path is open to you if you can demonstrate prior academic research experience or relevant industrial research / R&D experience.
Evidence may include peer-reviewed publications, conference or journal papers, preprints or manuscripts under review, an undergraduate or graduate thesis, a university research assistantship, a substantial faculty-supervised project, a research internship elsewhere, industrial AI/ML or advanced R&D work, strong technical reports, meaningful open-source research contributions, or comparable reproducible research projects.
Research potential can be demonstrated in more than one way, and publications are not required. A published paper is strong evidence and is genuinely valued — but a rigorous thesis, a serious industrial R&D record, or a well-executed reproducible project can demonstrate the same underlying ability. Tell us what you have done and we will assess it on its merits.
Your Research Journey at InfoLab
Graduate research follows a recognisable arc. Early on you will be guided closely; by the end you should be setting the direction yourself. Mentorship is active throughout, but intellectual ownership progressively becomes yours.
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1
Orientation and literature
Read deeply into a research area, reproduce key results, and learn to identify what is genuinely unsolved rather than merely unpublished.
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2
Problem formulation
Turn a broad interest into a precise, falsifiable research question with a defensible evaluation plan.
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3
Methodology and implementation
Design an approach, implement it properly, and build experiments that could actually disconfirm your hypothesis.
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4
Rigorous experimentation
Baselines, ablations, statistical care, and honest negative results. This is where most of the real work happens.
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5
Writing and submission
Work toward first-author papers at strong international venues, with detailed feedback on argument and presentation. We support you through submission and rebuttal; no one can promise acceptance.
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6
Thesis and independence
Assemble a coherent body of work into a dissertation, and prepare for the next stage — academic, industrial research, or your own direction.
Application Materials
Required
- Curriculum vitae, including your education, research experience, and technical skills.
- Academic transcript with GPA.
- Intended program — M.S./Ph.D. Combined or Ph.D.
- Intended admission semester.
- A short research-interest statement (roughly one page — see below).
- A concise explanation of why InfoLab specifically, rather than any lab working on AI.
What your research statement should cover
- Your previous academic, research, or industrial experience — and what you personally contributed.
- The research topics you want to pursue, stated concretely.
- Why those topics align with InfoLab's current work.
- The technical skills you would bring on day one.
- Your evidence of research potential, in whatever form it takes.
Name 1–3 specific InfoLab papers, projects, or research topics that connect to your interests, and explain the connection in a few sentences each. This single requirement is the clearest signal we receive. Applications that could have been sent unchanged to fifty other laboratories are unlikely to receive a reply.
Optional, and strongly recommended where available
- Google Scholar profile, publications, or preprints.
- GitHub, open-source contributions, or a technical portfolio.
- Personal or research website.
- Undergraduate or master's thesis, or substantial research reports.
- Evidence of industrial R&D work, where shareable.
Selection Process
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1
Application screening
We review your CV, transcript, research statement, and supporting evidence.
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2
Research-fit evaluation
We assess how your interests and preparation map onto active research directions and available supervision capacity.
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3
Interview
A discussion with Prof. Abuhmed, typically online for international applicants, covering your background and research interests.
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4
Technical or research discussion
Where appropriate, a deeper technical conversation or a small research task related to your stated interests.
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5
Research internship — only when useful
For some candidates we may suggest an internship period first, as a mutual evaluation. This step is optional. Applicants with demonstrated academic or industrial research experience routinely proceed directly to admission without it.
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6
Official graduate admission
Successful candidates apply through the SKKU Graduate School and must satisfy the university's official admission requirements. Support from the lab does not replace or bypass that process — check the official pages for current requirements, documents, and deadlines.
Other Opportunities
Research Interns
Undergraduate and visiting internships for students who want hands-on research experience — whether or not they later apply to our graduate programs. Also the natural route for candidates following Path A above.
Postdoctoral Researchers
Openings depend on active grants. A strong publication record in security, machine learning, or biomedical AI is expected. Enquire with a CV and a short statement of your research direction.
Research Developers
Engineering-focused roles building the systems, datasets, and tooling behind our research projects.
Frequently Asked Questions
Are M.S.-only positions available?
No. Standalone M.S. positions are not available at this time. We are recruiting for the M.S./Ph.D. Combined and Ph.D. programs only.
Which graduate programs are currently recruiting?
M.S./Ph.D. Combined and Ph.D.
Are the positions funded?
Yes. Graduate researchers in these programs receive a full tuition fee waiver and a monthly stipend, together with research computing resources, mentorship, and support for publication-oriented work.
Is an InfoLab internship mandatory?
No. An internship is preferred in some cases but not required. It is most useful for candidates with limited formal research experience, or for anyone who wants to evaluate research fit before committing.
Can I apply directly without an InfoLab internship?
Yes — particularly if you can demonstrate prior academic research experience or relevant industrial research and development experience. See Path B above.
Do I need publications to apply?
No. Publications are strong evidence of research ability and are genuinely valued, but they are not the only way to demonstrate research potential. A thesis, a research assistantship, industrial R&D work, technical reports, or serious reproducible open-source research can all serve as evidence.
Can international students apply?
Yes. InfoLab is an international research group and international applicants are explicitly welcome — our current researchers come from many countries. Applications are handled through SKKU's international graduate admissions.
Do I need to speak Korean?
Research and publication in the lab are conducted in English, and Korean proficiency is not required to do research with us. Formal language requirements for admission are set by the university, not the lab — check the SKKU Graduate School admissions pages for the requirements that apply to your program and nationality.
When should I apply?
Contact the lab well in advance of the SKKU Graduate School application deadline for your intended semester — several months ahead is sensible, since research-fit evaluation and any interview take time. Official deadlines and document requirements are published by the university, so check the admissions pages for current dates.
Can undergraduate students apply for internships?
Yes. Research internships are open to undergraduate and visiting students, and are a separate track from graduate recruitment. An internship is not an admission decision, and admission does not require one — but for some candidates it is a useful step toward it.
What if my background is unconventional?
Tell us about it. We care about demonstrated research ability and fit with our research directions. Candidates from industry, from adjacent disciplines, or with non-linear academic histories are assessed on the same basis as anyone else.
Apply
If you have read this far and the research areas genuinely match what you want to work on, we would like to hear from you.
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1
Read our research first
Go through our projects and publications, and pick the 1–3 papers or topics closest to your interests.
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2
Prepare your materials
CV, transcript, research-interest statement, intended program and semester, and any evidence of research or R&D experience — as listed under Application Materials.
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3
Email Prof. Tamer Abuhmed
Send everything in a single email, with the subject line:
[Graduate Application] Ph.D. — Your Name
or [Graduate Application] MS/PhD Combined — Your NameFor internships, use [Internship Application] — Your Name. A clear subject line means your message is read as an application rather than filtered as an enquiry.
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4
Apply to the Graduate School
Successful candidates then apply through SKKU Graduate School admissions, naming InfoLab and Prof. Abuhmed in the application.