Doctoral student in models, algorithms, and optimization for machine learning Full-time

Doctoral Student In Models, Algorithms, And Optimization For Machine Learning

We invite applications from talented and highly motivated candidates to pursue a PhD in machine learning at KTH, Sweden, and NTU, Singapore. This is a fully funded, joint doctoral position that will lead to a joint PhD degree awarded by KTH and NTU. The successful candidate will be supervised by professor Aristides Gionis (KTH), associate professor Kelly Ke Yiping (NTU), and assistant professor Sebastian Dalleiger (KTH). The doctoral student will be recruited and formally enrolled at KTH, and will be required to spend a minimum of 12 months at NTU in Singapore as part of the joint program.

The research project is broadly situated in the field of machine learning. Potential research topics include, but are 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.

Applicants must hold a Master of Science degree by the time of enrollment. Successful candidates should be highly self-motivated and committed to publishing and presenting high-quality research. Solid background in algorithms design, machine learning, and optimization is essential, along with strong programming and implementation skills.

Supervision: Aristides Gionis (KTH), Sebastian Dalleiger (KTH), Kelly Ke Yiping (NTU) are proposed to supervise the doctoral student. Decisions are made on admission.

To be admitted to postgraduate education, the applicant must have basic eligibility in accordance with either of the following:

• passed a second cycle degree (for example a master's degree), or
• completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
• acquired, in some other way within or outside the country, substantially equivalent knowledge

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.

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:

• independently pursue his or her work
• collaborate with others,
• have a professional approach and
• analyze and work with complex issues.
• Applicants must hold or be about to receive a Master of Science degree in computer science, machine learning, AI, data science, or a related area.
• Applicants must have strong academic credentials, demonstrated by excellence in course work or relevant projects.

After the qualification requirements, great emphasis will be placed on personal skills.

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.

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.

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