伦敦大学学院、香港科技大学（广州）最新PhD奖学金项目信息分享！

本期为大家推荐伦敦大学学院、香港科技大学（广州）2026最新奖学金项目介绍。

1、伦敦大学学院

TRUST: Transparent, Responsible, User-centred Sexual-health Technologies using Natural Language Processing

University College London | UCL Global Business School for Health

截止时间：January 26, 2026 周一

资助的博士项目（全球学生）

About the Project

You will join a hands-on supervisory team at the Global Business School for Health (GBSH), working at the intersection of computer science, human–computer interaction and clinical sexual health. The project sits within an active lab on safe and robust clinical AI and links closely to behavioural science, psychology and digital health communication. We meet regularly, agree focused research plans and support targeted outputs and career development from day one, including journal papers, conference presentations and portfolio pieces for academic and industry careers.

BACKGROUND:

Sexual difficulties are common. The British National Survey of Sexual Attitudes and Lifestyles reports that around half of women and two-fifths of men experience distress linked to erection difficulties, low libido, pain or orgasm difficulties. Many people hesitate to seek professional advice because of stigma, privacy concerns and uncertainty about whether help is possible or effective. Evidence shows that tailored digital sex therapy can be effective, yet there is still an unmet need for secure, trustworthy self-help advice that complements NHS services. At the same time, people are increasingly turning to general-purpose AI systems for sexual health advice, even though these tools were not designed for this setting and can generate unsafe, misleading or insensitive responses.

This PhD will explore how to design and deploy a privacy-preserving self-help AI system that provides evidence-based guidance and signposting for adults with sexual difficulties. The focus is on safe and responsible use of natural language processing (NLP) to support people to understand their concerns, try evidence-based strategies and, where appropriate, seek care from their GP or other medical professionals. The project will be co-created with stakeholders, people with lived experience and potential end users so that its design, safeguards and governance reflect real needs and values. Technically, you will develop an NLP stack tailored to sensitive health contexts, for example using retrieval-augmented generation, safety layers to reduce harm and misinformation risks, red-flag detection with rule-backed signposting and transparent explanations to support user trust. Robustness will be assessed through targeted test suites and adversarial evaluations of safety, calibration and refusal behaviour, leading to publishable evidence and a prototype for a theoretically informed, ethical and clinically safe generative AI tool.

AIMS:

The overarching aim is to design, build and evaluate responsible AI approaches that support evidence-based, user-centred self-help for sexual difficulties, with scope for the student to shape the technical emphasis. The project will move from co-design and requirements gathering with people with lived experience and clinicians, through technical development and validation of NLP and interaction approaches, to user evaluation and an implementation roadmap aligned with NHS pathways and governance requirements.

METHODOLOGY:

A mixed-methods approach combining literature review, co-design activities and interviews with people with lived experience, clinicians and other stakeholders; development and evaluation of an NLP pipeline in Python using appropriate large language models, retrieval components and safety layers; and qualitative and quantitative user evaluation, including usability testing and usage analytics.

TIMELINE:

• Year 1: Foundations and framing, including core training, scoping reviews, early stakeholder interviews, initial requirements and safety criteria, governance and data protection planning, ethics submissions and a first prototype.
• Year 2: Technical development and user studies, including iterative development of models, retrieval and safety components, user and stakeholder studies on usability, adoption and governance, and interim dissemination.
• Year 3: Consolidation and translation, including final optimisation and robustness checks, further usability work and, where feasible, external evaluations, manuscripts and conference submissions, thesis writing and an implementation roadmap.

ABOUT YOU:

We are keen to hear from candidates with a strong background in computer science, engineering, data science, human–computer interaction, applied mathematics or related quantitative disciplines, including clinicians or health researchers who can code confidently.

Essential

• A master’s degree in a relevant field, or equivalent experience, with strong Python programming and applied machine learning skills.
• Practical experience building end-to-end machine learning or NLP workflows, including data preparation, training and evaluation.
• Ability to write clear, modular and maintainable code, and willingness to adopt good software engineering practice such as version control, tests and documentation.
• Good experiment hygiene, including clear baselines, checks for overfitting, appropriate validation procedures and attention to reproducibility.
• Familiarity with GitHub or GitLab and collaborative development practices.
• Clear academic writing and ability to plan workstreams and meet deadlines.
• Motivation to work across disciplines and with stakeholders, including people with lived experience, clinicians and behavioural scientists.

Desirable

• Experience with health or behavioural science contexts, including qualitative methods and user studies.
• Familiarity with NLP tooling and evaluation, especially for sensitive or safety-critical topics.
• Experience with testing frameworks, experiment tracking tools or continuous integration in an ML context.
• Evidence of dissemination, such as preprints, posters, talks or open-source contributions.

WHAT WE OFFER:

This studentship provides a starting stipend of £23,466 per annum and covers the cost of tuition fees based on the Overseas rate.

HOW TO APPLY:

Enquiries regarding the post can be made to Sharleen Young (sharleen.young@ucl.ac.uk)

To apply, please send 1.) a current two-page CV, 2.) a one-sided A4 motivation letter, 3.) copy of transcripts and diploma and 4.) the contact details of two professional referees to Sharleen Young (sharleen.young@ucl.ac.uk). Please use the following subject line: PhD application “TRUST: Transparent, Responsible, User-centred Sexual-health Technologies using Natural Language Processing”.

Closing deadline for applications: 23:59 Monday 26th January 2026 (GMT summertime)

Interview date/s: TBC

Applications that are submitted without following the correct application process, or those exceeding the page limits for CV’s and motivation letters will not be considered. The successful applicant will subsequently be required to apply to and register on the Global Healthcare Leadership and Management MPhil/PhD to take up the studentship.

2、香港科技大学（广州）

PhD in Data Science and Analytics

截止日期：15 Jun 2026

资助的博士项目（全球学生）

PhD in Data Science and Analytics

Guangzhou, China

DURATION: 4 years, up to 8 years

LANGUAGES: English

PACE: Full time, Part time

APPLICATION DEADLINE: 15 Jun 2026

TUITION FEES: CNY 40,000 / per year for scholarship awardees, all full-time students will be automatically considered for scholarship.

CNY 150,000 / per year for part-time students.

Key Summary

About:

The PhD in Data Science and Analytics program focuses on advanced research in data science, incorporating statistical analysis, machine learning, and data visualization. Students will develop strong analytical and computational skills, allowing them to address complex real-world problems. This program is tailored for those interested in contributing original research to the field. Students can expect to benefit from a supportive academic environment with access to cutting-edge resources and technology.

Career Outcomes:

Graduates can pursue various career paths, including roles as data scientists, analysts, and researchers in diverse sectors such as technology, finance, and healthcare. Opportunities may also arise in academia, consulting, or policy-making, where strong analytical and research skills are valued.

Introduction

In the digital era, following advancements made in innovative technologies, data handling is growing at an unprecedented pace. The data-driven world opens tremendous possibilities and opportunities for companies and businesses across all industries, as they can make use of the data to create value for their business. As a disruptive consequence of the digital revolution, data science and analytics have become an emerging and cross-disciplinary field that requires knowledge and skills in many areas, such as computer science, statistics, and mathematics.

The Doctor of Philosophy (PhD) Program in Data Science and Analytics aims to facilitate close integration of statistical analytics, logical reasoning, and computational intelligence in the study of data processing and analytics. The programs will provide rigorous research training that prepares students to become knowledgeable researchers who are conversant in applying logic, mathematics, algorithms, and computing power in the process of examining and analyzing data in academia or industry so as to derive valuable insights for making better decisions.

The PhD Program aims to develop the skills needed for students to identify theoretical research issues related to practical applications, formulate and undertake research that addresses issues identified, and independently find a data science and analytics-related solution. A PhD graduate is expected to demonstrate mastery of knowledge in the discipline and to synthesize and create new knowledge, making an original and substantial scientific contribution to the discipline.

To qualify for admission, applicants must meet all of the admission requirements (Bachelor degree + English Proficiency). Admission is selective, and meeting these minimum requirements does not guarantee admission. For more details, please visit https://www.findaphd.com/common/clickCount.aspx?theid=0&type=185&url=https%3a%2f%2ffytgs.hkust-gz.edu.cn%2fadmissions%2fbefore-submitting-an-application%2fadmission-requirements