PhD Researcher - AI TokCart / PhD Researcheress - AI TokCart

ETH Zurich - April 24, 2026

PhD Researcher - AI TokCart

100%, Singapore, fixed-term

The Singapore-ETH Centre was established in 2010 by ETH Zurich - The Swiss Federal Institute of Technology and Singapore's National Research Foundation (NRF), as part of the NRF’s CREATE campus. As ETH Zurich's only research centre outside of Switzerland, the centre has bolstered the research capacity of ETH Zurich to develop sustainable solutions to global challenges in Switzerland, Singapore, and surrounding regions.

Situated in a rapidly urbanising region, the Singapore-ETH Centre aims to offer practical solutions to some of the most pressing challenges in urban sustainability, resilience, and health through its programmes: Future Cities Lab Global (FCL Global) and Future Health Technologies (FHT).

The centre serves as an intellectual hub for research, uniting principal investigators and researchers from diverse disciplines and backgrounds. To foster the exchange of ideas and expertise, our researchers actively collaborate with universities and research institutes and engage with industry and government agencies to translate knowledge into practical solutions for real-world problems.

Project Background

The healthcare systems of the future must effectively harness data to support clinicians, allowing them to prioritize patient care while utilizing AI to detect patterns beyond human perception, enhance diagnostic accuracy, optimize workflows, and improve risk assessment and communication. Developing AI models that address these needs is particularly urgent in ageing societies, where increasing patient numbers coincide with heightened workforce constraints.

A significant contributor to disability in older adults is impaired musculoskeletal (MSK) health, with fall-related fractures representing a central research focus for our group. Despite their considerable socioeconomic burden, progress in prevention and screening has been limited, largely because fall and fracture risks are often tackled independently, despite their interconnected underlying mechanisms. A promising direction for AI in healthcare is the seamless integration of clinical image-based foundation models that can be fine-tuned across multiple use cases.

In this project, we aim to develop cross-modal AI models for MSK health evaluation by linking diverse clinical imaging datasets. The central innovation is the creation of a shared, tokenized latent space that enables data translation, risk modeling, and local deployment, even in settings with limited imaging data. Particular emphasis will be placed on integrating advanced biomechanical markers of bone health into AI workflows, supporting more precise and clinically actionable risk assessment.

Job Description

The PhD candidate will join a team of researchers focused on developing large medical image-based AI models for managing MSK health.

  • Pretraining, adapting, and evaluating foundation models for medical image data using self-supervised and multimodal representation learning.
  • Developing cross-modal image modeling methods, including cross-modal translation, multimodal fusion, and related generative or representation-learning approaches.
  • Evaluating the learned models on clinically relevant downstream tasks, such as bone health assessment, anatomical and biomechanical biomarker estimation, and fracture-risk-related prediction.
  • Co-supervision of MSc and BSc students.

Please note that the employment will be at the Singapore-ETH Centre in Singapore, and local working regulations will apply.

Funding is provided for up to four years. Upon successful completion of studies, the PhD degree will be awarded by ETH Zurich.

Profile

  • Applicants should hold an MSc degree and possess a strong background in computer science, engineering, mathematics, physics, or a related quantitative discipline.
  • Candidates should be capable of working largely independently on complex research topics and demonstrate strong motivation.
  • We are particularly interested in applicants with a solid foundation in machine learning and AI, image processing, strong Python programming skills, and experience in software development.
  • Background knowledge in parallel computing or high-performance computing is desirable.
  • Experience with software engineering practices, including version control (e.g., git) and collaborative development workflows, is required.
  • Applicants must be proficient in written and spoken English.

Workplace

We Offer

  • Accredited with 5 Tripartite Standards by Tripartite Alliance for Fair & Progressive Employment Practices (TAFEP) Singapore.
  • A diverse workplace with 32 nationalities, offering ample opportunities for mutual learning.
  • Positive and inclusive working environment.
  • 25 days of annual leave for fixed-term contracts.
  • 1 day of Birthday Leave.
  • Annual dental benefits.
  • Committed to being a supportive employer as you prioritize your physical and mental wellness.
  • Comprehensive healthcare insurance coverage.
  • Flexible hybrid work arrangement (up to 2 days per week from home).
  • Abundant networking opportunities across various disciplines.
  • Accredited with NS mark certification.

The Singapore-ETH Centre is an equal opportunity and family-friendly employer. All candidates will be evaluated on their merits and qualifications, without regard to gender, race, age, or religion.

We Value Diversity and Sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity, and nurture a working and learning environment where the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to learn how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us; we consistently work towards a climate-neutral future.

Curious? So Are We.

We look forward to receiving your online application using the form below.

Please include the following documents:

  • A cover letter detailing your motivation for the project.
  • Your CV, including the name and contact information of two references.
  • A copy of your university transcripts as PDFs.

Further information about the Singapore-ETH Centre can be found on our website. Questions regarding the position should be directed to Dr. Benedikt Helgason at bhelgason@ethz.ch.

Only applications matching the job profile will be considered.

Location : Zürich
Country : Switzerland

Application Form

Please enter your information in the following form and attach your resume (CV)

Only pdf, Word, or OpenOffice file. Maximum file size: 3 MB.