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University College London Machine Learning Scholarship USA

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University College London is proud to announce the UCLFAA Machine Learning Scholarship (USA) for the academic year 2026, funded by the UCL Friends and Alumni Association. This scholarship is designed to support US citizens typically domiciled in the United States who wish to pursue eligible master’s programmes in Machine Learning at UCL.

University College London, commonly known as UCL, was founded in 1826 in London, England. It was one of the first universities in the UK to welcome students regardless of religion or social background and was also among the first to admit women on equal terms with men. Over the years, UCL has become a world-leading university known for excellence in research, innovation, medicine, engineering, and social sciences.

Table of Briefs

Scholarship Details Information
Scholarship Name UCLFAA Machine Learning Scholarship (USA)
Provider UCL Friends and Alumni Association
University University College London
Study Level Master’s Degree
Eligible Nationality US Citizens
Scholarship Value USD $20,000
Funding Type Tuition fee credit or monthly instalments
Eligible Courses Machine Learning-related MSc programmes
Application Deadline 4 June 2026
Study Destination United Kingdom

Background

The UCLFAA Machine Learning Scholarship was established to support academically talented students from the United States who wish to pursue postgraduate education in machine learning and related fields at UCL. The scholarship reflects the strong relationship between UCL and its alumni and friends network in the USA.

As industries increasingly depend on artificial intelligence, data analysis, and automation technologies, skilled professionals in machine learning are in high demand worldwide. Through this scholarship, UCL aims to encourage future innovators and researchers by providing financial assistance for specialised postgraduate study.

Eligibility Criteria

To apply for the UCLFAA Machine Learning Scholarship, applicants must generally meet the following requirements:

  • Must be a US citizen
  • Typically domiciled in the United States
  • Must apply for an eligible Machine Learning master’s course at UCL
  • Must meet the academic admission requirements for the selected programme
  • Should demonstrate strong academic potential and interest in machine learning or data science

Applicants are advised to carefully review the official scholarship application form for complete eligibility details and additional requirements.

Benefits

The UCLFAA Machine Learning Scholarship provides funding worth:

  • USD $20,000
  • Paid either:
    • As a direct credit toward tuition fees, or
    • Through monthly instalments

Additional Benefits

Students may also benefit from:

  • Access to UCL’s global research community
  • Networking opportunities with industry experts
  • Career support and employability services
  • Exposure to advanced AI and machine learning research
  • International study experience in London

Application Process

Students interested in this scholarship should follow these steps:

Step 1: Choose an Eligible Course

Select one of the approved Machine Learning MSc programmes at UCL.

Step 2: Apply for Admission

Submit an application for admission to the chosen master’s course through UCL’s postgraduate application system.

Step 3: Complete the Scholarship Application

Fill out the UCLFAA Machine Learning Scholarship Application Form with all required information and supporting documents.

Step 4: Submit Before the Deadline

Ensure that all materials are submitted before the official closing date.

Important Dates

Application Deadline: 4th June 2026.

Conclusion

The UCLFAA Machine Learning Scholarship (USA) 2026 is an excellent opportunity for US students aiming to study advanced machine learning subjects at one of the UK’s top universities. With generous financial support worth USD $20,000 and access to world-class education at UCL, this scholarship can significantly support students pursuing careers in AI and data-driven technologies.

Apply Now

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