KTH Royal Institute of Technology

<h3><strong>Project description</strong></h3>
<p><strong>Third-cycle subject:</strong> Computer Science</p>
<p>KTH is now inviting talented and highly motivated candidates to apply for this doctoral position. The doctoral student will develop new algorithms and well-founded methods, formalize their theoretical foundations, and evaluate them experimentally. The research will be broadly situated in machine learning, including (but not limited to) algorithmic knowledge discovery, graph mining and social network analysis, optimization for machine learning, representation learning, and fair, accountable, and transparent machine learning.</p>
<p>This PhD position in machine learning, will lead to a joint doctoral degree from KTH Royal Institute of Technology (Sweden) and Nanyang Technological University (NTU, Singapore). The successful candidate will be enrolled as a doctoral student at KTH and will spend at least 12 months at NTU as part of the program.</p>
<p><strong>Supervision:</strong> Aristides Gionis (KTH), Sebastian Dalleiger (KTH) and Kelly Ke Yiping (NTU)</p>
<h3><strong>Admission requirements</strong></h3>
<p>To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:</p>
<ul>
<li>passed a second cycle degree (for example a master's degree), or</li>
<li>completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or</li>
<li>acquired, in some other way within or outside the country, substantially equivalent knowledge</li>
</ul>
<p>The candidate must be able to commit to a minimum 12-month research stay at NTU in Singapore. This is a requirement for this specific position.</p>
<p>In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.</p>
<h3><strong>Selection</strong></h3>
<p>In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:</p>
<ul>
<li>independently pursue his or her work</li>
<li>collaborate with others,</li>
<li>have a professional approach and</li>
<li>analyze and work with complex issues.</li>
</ul>
<p>The Applicant must hold or be about to receive a Master of Science degree in computer science, machine learning, AI, data science, or a related area.</p>
<p>Applicants must have strong academic credentials, demonstrated by excellence in course work or relevant projects.</p>
<p>The ideal candidate is highly motivated with a solid background in one or more of the following areas: algorithm design, machine learning, mathematical optimization, and learning theory. The candidate should also have strong programming skills for implementing and benchmarking algorithms, and be self-driven and committed to producing and presenting high-quality research at top-tier venues such as NeurIPS, ICML, ICLR, and KDD.</p>
<p>After the qualification requirements, great emphasis will be placed on personal skills.</p>
<h3><strong>Target degree: Doctoral degree</strong></h3>
<h3><strong>Information regarding admission and employment</strong></h3>
<p>Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time. In the case of studies that are to be completed with a licentiate degree, the total period of employment may not be longer than what corresponds to full-time doctoral education for two years.</p>
<p>As a doctoral student, you are entitled to a workplace with many employee benefits and monthly salary according to KTH’s Doctoral student salary agreement. Read more about Doctoral studies (PhD) | KTH | Sweden.</p>
<h3><strong>Union representatives</strong></h3>
<p>Contact information forunion representatives.</p>
<h3><strong>Doctoral Student’s network (Students’ union on KTH Royal Institute of Technology)</strong></h3>
<p>Contact information forPhD chapter.</p>
<h3><strong>To apply for the position</strong></h3>
<p>Apply for the position and admission through KTH's recruitment system. It is the applicant’s responsibility to ensure that the application is complete in accordance with the instructions in the advertisement.</p>
<p>Applications must include the following elements:</p>
<ul>
<li>Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above). Translations into English or Swedish if the original document is not issued in one of these languages.Copies of originals must be certified.</li>
<li>CV including your relevant professional experience and knowledge.</li>
<li>Application letter with a brief description of why you want to pursue research studies, about what your academic interests are and how they relate to your previous studies and future goals. (Maximum 2 pages long)</li>
<li>Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.</li>
</ul>
<p>Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/Central European Summer Time).</p>
<h3><strong>Other information</strong></h3>
<p>For information about processing of personal data in the recruitment process.</p>
<p>It may be the case that a position at KTH is classified as a security-sensitive role in accordance with the Protective Security Act (2018:585). If this applies to the specific position, a security clearance will be conducted for the applicant in accordance with the same law with the applicant's consent. In such cases, a prerequisite for employment is that the applicant is approved following the security clearance.</p>
<p>We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.</p>
<p>Disclaimer: <em>In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.</em></p>
<p>Join us at KTHKTH shapes the future through education, research and innovation. As a leading international technical university, we play an active role in advancing the transition towards a sustainable society. At KTH, you have the opportunity to grow and develop in a creative and dynamic environment, with good working conditions and attractive benefits. Equality, diversity and equal opportunities are essential to quality and form an integral part of KTH’s core values as a university and public authority. Learn more about our benefits and what it's like to work and grow at KTH</p>
<p>Anställningsform: tidsbegränsad anställning | Anställningens omfattning: heltid | Antal lediga befattningar: 1 | Sysselsättningsgrad: 100% | Ort: Stockholm | Län: Stockholms län | Land: Sweden | Referensnummer: PA-2026-3210 | Kontakt: Aristides Gionis , Aristides Gionis , | Publicerat: 2026-10-01 | Sista ansökningsdag: 2026-10-22</p>


Doctoral student in machine learning and optimization

Doctoral student in machine learning and optimization

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