United Kingdom – PhD in Machine Learning at Queen’s University
Listed on 2026-02-14
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IT/Tech
Data Scientist, Machine Learning/ ML Engineer -
Education / Teaching
Data Scientist
University: Queen’s University Belfast
Country: United Kingdom
Deadline: Not specified
Fields: Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering
Are you eager to push the boundaries of machine and deep learning while building a strong foundation for a research-driven career in artificial intelligence? If you have a passion for innovative problem-solving, programming prowess, and the ambition to work at the forefront of technology, this opportunity at Queen’s University Belfast could be the perfect next step in your academic journey.
About The University Or Research InstituteQueen’s University Belfast, located in the vibrant capital city of Northern Ireland, is a member of the prestigious Russell Group of UK research-intensive universities. Established in 1845, Queen’s University is renowned for its world‑class teaching, impactful research, and a diverse, international community. The university consistently ranks among the top institutions in the United Kingdom and is recognized globally for its excellence in engineering, computer science, and life sciences.
The campus blends historic architecture with state‑of‑the‑art research facilities, fostering an environment where innovation thrives and students are encouraged to excel academically and professionally. Belfast itself is a dynamic city, known for its cultural heritage, affordable living, and welcoming atmosphere, making it an ideal destination for international scholars.
The PhD position focuses on the rapidly advancing fields of machine learning and deep learning. These disciplines are at the heart of modern artificial intelligence, driving transformative changes across industries such as healthcare, finance, autonomous systems, and more. As the demand for intelligent systems that can learn from data and make informed decisions continues to grow, research in these areas remains critically important.
By contributing to the development of new algorithms, models, and applications, PhD candidates at Queen’s University Belfast will play a vital role in shaping the future of AI technology and its real‑world impact.
This PhD opportunity is supervised by Dr. Awais Rauf, an active researcher in the field of machine learning. The research will involve working on cutting‑edge topics in machine and/or deep learning, providing candidates with the chance to engage in high‑impact projects and collaborate with a team of experienced scholars. The specific research focus can be tailored to the candidate’s background and interests within the broader scope of artificial intelligence, ensuring a challenging yet rewarding doctoral experience.
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- A strong academic background in computer science, data science, electrical engineering, or a closely related field.
- Demonstrated expertise in machine learning and/or deep learning.
- Excellent programming skills, with experience in relevant languages and frameworks.
- A high level of motivation and a genuine interest in advancing the state of the art in AI research.
- Good GPA, as required by the School.
- Proficiency in English, demonstrated by a valid TOEFL or IELTS score, as per university admission requirements.
Interested candidates are encouraged to email their details, including a CV and relevant experience, directly to Dr. Awais Rauf. Please refer to the official advertisement for application details.
For more information, you can view the original Linked In post by Dr. Awais Rauf:
ConclusionThis is an exceptional opportunity for aspiring researchers to join a leading university and contribute to groundbreaking advancements in machine and deep learning. If you are driven by curiosity and a desire to make a meaningful impact in the field of artificial intelligence, consider applying for this PhD position at Queen’s University Belfast. Stay tuned for more opportunities like this by following updates from academic networks and professional platforms.
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