PhD candidate 'Development of an integrated system for breast cancer imaging | focus point X-ray'

Radboud University Medical Center (Radboudumc); Nijmegen; On-site; EUR 50,000 - 65,000; Full time

Benefits offered by this job

Travel allowance

Public transport reimbursement

Home-working days

Holiday allowance

Year-end bonus

Irregular hours allowance

Vacation hours

Monthly changing allowance

Salary increases

Job summary

Radboudumc seeks a creative researcher to advance joint tomosynthesis and ultrasound imaging. You will handle data preprocessing and the core reconstruction work, validating with phantoms and guiding early patient images.

You will collaborate closely with a PhD student and industry partners for translation and clinical evaluation. Applicants should hold an MSc in a physical or engineering field, with experience in image processing, modelling or inverse problems, and proficiency in Python, C/C++,

Qualifications

• MSc or equivalent in a quantitative field such as physics, maths, CS, engineering or medical physics.
• Experience with physics modelling, inverse problems or image processing is desirable.
• Proficiency in Python, C/C++, MATLAB or similar and strong English communication.

Responsibilities

• Work on x-ray data preprocessing and joint reconstruction for tomosynthesis and ultrasound.
• Validate methods with digital and physical phantoms; aim for first patient images.
• Collaborate with the ultrasound-focused PhD student and industry partners for clinical evaluation.

Skills

Physics modelling

Inverse problems

Image processing

Python

C/C++

MATLAB

English communication

Education

MSc in physics / mathematics / computer science / engineering / medical physics

Tools

Python

C/C++

MATLAB

Job description

Job description

Ultrasound and tomosynthesis are the most prevalent modalities used for breast imaging, and each has its specific advantages and disadvantages. Tomosynthesis uses x rays to create a pseudo-3D representation of the breast with high in-plane spatial resolution, but low out-of-plane (depth) resolution. Ultrasound uses sound waves to create a cross-sectional image of the tissue and has excellent depth resolution, but limited resolution in directions perpendicular to the transmitted ultrasound lines.

We plan to develop a joint system that will use the information from each modality to improve the image quality of the other, yielding not only a multi-modality imaging system, but a joint imaging system. The combination of tomosynthesis and ultrasound into a single joint imaging system will yield improved images from two independent and complementary sources, with inherent spatial correlation, allowing for improved lesion detection, even in dense breasts, and the direct multi-modal assessment of suspicious lesions. For this multi-disciplinary project, we will be working in collaboration with the Medical UltraSound Imaging Center (MUSIC) lab of our Department, who will be developing the ultrasound aspects of this system (see accompanying vacancy).

In this project you will focus on the x-ray related data preprocessing and on the joint reconstruction itself. You will validate these using both digital and physical phantoms, working towards first patient images at the end of the project. All of this will be in collaboration with a PhD student focusing on the ultrasound aspects of the project, and industry partners to facilitate the translation of these methods into clinical evaluation. Tasks will also include presenting at international scientific conferences and writing papers on the newly developed methods and study results.

Requirements

• You should be a creative and enthusiastic researcher with a MSc degree in physics, mathematics, computer science, engineering, medical physics, or similar.
• Experience or interest in physics modelling, inverse problems, and/or image processing, and affinity with biomedical research.
• Experience in programming in python, C/C++, Matlab, or similar.
• Excellent communication skills in English, both written and spoken.

Conditions of employment

Fixed-term contract: 4 years.

Benefits

• You will receive a €0.18 per kilometer travel allowance.
• Public transport costs (2nd class) are fully reimbursed.
• If you work partly or entirely from home, you will receive €2.40 per home-working day.
• 8% holiday allowance.
• 8.3% end-of-year bonus.
• An irregular hours allowance ranging from 47% to 72%.
• You are entitled to 176 vacation hours per year (based on a 36-hour work week).
• You will receive a changing allowance of €80 gross per month for a full-time position.
• Your salary will increase by 3.5% as of July 1, 2026, and an additional 3.5% as of May 1, 2027.

Flexible benefits scheme With our flexible benefits scheme, you decide how to use part of your employment benefits. Purchase extra leave days or use your year-end bonus to buy a bicycle with tax benefits. You choose what suits you best.

Warm welcome We believe a good start is important. Thanks to our onboarding app, you’ll be well prepared even before your first working day. During the introduction day, you’ll get to know your colleagues and our organization.

Work–life balance We consider a healthy work–life balance essential. Through inspiring training sessions, mindfulness activities, and caregiver consultation hours, we support you in every phase of your life.

Growth and development Our online learning environment offers a wide range of training courses, e-learnings, and educational programs—from professional specialization to personal development. This allows you to keep growing and make the most of your talents.

Employer

Radboudumc Welcome to Radboud university medical center (Radboudumc), where our research groups strive for innovative solutions that make impact on health and healthcare. We challenge the status quo to overcome current and future health challenges. Our goal is to shape the future of healthcare for generations to come. Our focus is on prevention, sustainability, and meaningful care, which we achieve through our in-depth understanding of disease mechanisms, clinical science, public health research, medical technology and data science. Our approach is centered on breakthroughs that can truly enhance personalized healthcare and public health.

Department

Beeldvorming Place of work Nijmegen and the Radboudumc Nijmegen is the oldest Dutch city with a rich history and one of the liveliest city centers in the Netherlands. Radboud University has over 17,000 students. Radboud University Medical Center is a leading academic center for medical science, education, and health care with over 10,000 staff and 3,000 students.

Department of Medical Imaging

The Department of Medical Imaging is one of the most active research departments of the Radboudumc. More than 100 researchers are continuously striving to optimize healthcare. Close cooperation between preclinical researchers, radiologists, and clinicians gives a fantastic opportunity to implement new imaging techniques in clinical practice, and you will be working directly in this field.

Advanced X-ray Tomographic Imaging laboratory

The AXTI laboratory works on the development, optimization, and clinical evaluation of new x-ray-based imaging methods. The lab focuses on the use of medical physics approaches to improve image acquisition, reconstruction, and processing methods, including artificial intelligence algorithms, and to evaluate the clinical performance of new technology in new clinical applications. The group counts on members with wide-ranging expertise in image processing, reconstruction, deep learning and other AI methods, and analysis, as well as radiation dosimetry, along with the design and performance of patient trials. The laboratory works closely with radiologists and industry to develop new, clinically relevant, imaging methods and processes in x-ray-based imaging, especially in breast imaging and body CT, to have an impact in detection, diagnosis, and treatment of pathologies.