Post Doctoral Fellow

Khalifa University; Abu Dhabi; On-site; AED 240,000 - 360,000; Full time

Job summary

Khalifa University Enterprise in Abu Dhabi is seeking a Postdoctoral Research Fellow to lead quantitative medical image analysis projects, develop imaging biomarkers for fertility and women's health, and advance clinical translation of AI-based imaging tools. The role involves collaboration across academia, clinical partners, and industry, with a focus on reproducibility and ethical data handling.

The fellow will supervise PhD students and research staff, contribute to the radiomics platform,

Qualifications

• PhD in Biomedical Engineering, Medical Physics, Computer Science, or a closely related discipline.
• Demonstrated expertise in quantitative medical image analysis and artificial intelligence.
• Experience in algorithm development, radiomics, and imaging biomarker research.
• Track record of peer-reviewed publications in relevant areas.

Responsibilities

• Lead research and development within the local radiomics platform, integrating advanced quantitative imaging analysis and AI for multimodal medical images.
• Develop and validate imaging biomarkers for fertility and women's health, in partnership with clinical collaborators.
• Lead calibration and validation activities for quantitative CT imaging, including phantom development and harmonization strategies.
• Work collaboratively with cross-disciplinary teams, including academic, clinical, and industry partners.
• Support training and supervision of PhD students and research assistants.
• Disseminate research outcomes via publications, conferences, and stakeholder engagement.
• Ensure compliance with data management, reproducibility, and ethical standards.

Skills

Quantitative image analysis

Artificial intelligence

Algorithm development

Radiomics

Imaging biomarkers

Research collaboration

Mentoring

Publications

Academic collaboration

QS Top 200 university experience

Education

PhD in Biomedical Engineering / Medical Physics / Computer Science

Tools

Radiomics software

Imaging analysis tools

IBSI harmonization workflows

Job description

The Postdoctoral Research Fellow will lead research into quantitative medical image analysis, focusing on the development, standardisation, and clinical translation of imaging biomarkers through advanced artificial intelligence methodologies. The fellow will develop trustworthy quantitative imaging methods for precision medicine, contribute to local radiomics platform enhancements, and drive clinical collaborations, particularly with SEHA Fertility Care and international partners. The role will support the entire research process, from algorithm development to validation and deployment, and will play a key role in disseminating findings and supporting postgraduate training.

Position Requirements:

• Drive research and development within the local radiomics platform, integrating advanced quantitative imaging analysis and AI for multimodal medical images.
• Develop and validate imaging biomarkers for fertility and women's health, in partnership with clinical collaborators
• Lead calibration and validation activities for quantitative CT imaging, including phantom development and harmonization strategies.
• Work collaboratively with cross-disciplinary teams, including academic, clinical, and industry partners.
• Support the training and supervision of PhD students and research assistants engaged on the project.
• Disseminate research outcomes via publications, conferences, and stakeholder engagement.
• Ensure compliance with data management, reproducibility, and ethical standards.

Candidate Criteria

• PhD in Biomedical Engineering, Medical Physics, Computer Science, or a closely related discipline.
• Demonstrated expertise in quantitative medical image analysis and artificial intelligence.
• Experience in algorithm development, radiomics, and imaging biomarker research.
• Track record of peer-reviewed publications in relevant areas.
• Experience of undertaking assigned research tasks and starting to manage own workload
• A willingness to contribute to a collaborative and supportive team culture
• Experience with radiomics and quantitative image imaging software.
• Familiarity with IBSI standards and harmonization workflows.
• Collaborations with clinical or industrial partners.
• Experience in mentoring or supervising students.
• Research experience or academic training at a QS Top 200 university.