Doctoral Student in Machine Learning: KTH Royal Institute of Technology is offering a PhD scholarship in machine learning, specifically focusing on explainable clustering. This position is part of a dynamic research team led by Professor Aristides Gionis, addressing complex issues in data science and machine learning.
Doctoral Student in Machine Learning with Focus on Explainable Clustering
Designation
Position: Doctoral Student in Machine Learning
Department: School of Electrical Engineering and Computer Science
Research Team Lead: Professor Aristides Gionis
| Details | Information |
|---|---|
| Research Area | Machine Learning, Explainable Clustering |
| Location | Stockholm, Sweden |
| Type of Employment | Temporary, full-time |
| Salary | Monthly salary as per KTH’s agreement |
| Number of Positions | 1 |
Research Area
- Focus: Machine Learning with an emphasis on explainable clustering techniques.
- Topics of Interest: Knowledge discovery, statistical techniques for big data management, optimization for machine learning, analysis of information and social networks, fairness, accountability, and transparency in learning systems.
Location
City: Stockholm
Country: Sweden
Eligibility/Qualification
- A Master of Science degree in Computer Science, Data Science, or a related field.
- Strong background in algorithmic design, data mining, machine learning, and combinatorial optimization.
- Proven ability to publish high-quality papers and develop research prototypes.
- Proficient in English, both spoken and written.
Description
The applicant will engage in cutting-edge research and develop novel methods to extract knowledge from data within a supportive international environment. The position is funded by the Swedish Research Council (VR) and offers opportunities for collaboration with industry and premier institutions globally.
How to Apply
Interested candidates must submit the following documents through KTH’s recruitment system:
- CV detailing relevant professional experience.
- Copies of diplomas and transcripts from previous studies.
- Certificates demonstrating language proficiency.
- Representative publications or technical reports (with a summary and a web link for longer documents).
Note: Ensure the application is complete as per the advertisement instructions.
Last Date to Apply
Application Deadline: 06 March 2025, 11:59 PM CET/CEST
This structured format provides a comprehensive view of the scholarship opportunity, ensuring potential applicants have all necessary information to proceed.
