PhD Candidate 'AI-Driven Handheld Ultrasound for Military Trauma Care'

Job description

Do you want to develop artificial intelligence for medical imaging to improve care for injured military personnel?

Military trauma care takes place under challenging conditions. During military operations, medical resources may be limited, specialist expertise may not always be available, and evacuation to a hospital may take hours or even days. Under these circumstances, healthcare providers must be able to rapidly and reliably identify a patient’s injuries and determine the treatment required. Rapid diagnostics can be lifesaving.

Ultrasound offers significant opportunities in this regard. Portable ultrasound equipment enables healthcare providers to examine patients at the point of care, without relying on extensive diagnostic facilities. One important application is the Extended Focused Assessment with Sonography in Trauma (EFAST), which can be used to detect signs of internal bleeding and pneumothorax, among other conditions. However, performing and interpreting ultrasound examinations requires specific knowledge and experience, which may not be readily accessible in forward-deployed medical treatment facilities.

Can artificial intelligence make ultrasound more accessible and effective for military healthcare providers in operational environments?

This is the central challenge of this PhD research project. Ultrasound offers valuable opportunities for rapid, portable diagnostics in military trauma care, particularly in forward-deployed settings where access to advanced diagnostic equipment and specialised expertise may be limited.

You will investigate how artificial intelligence can support military healthcare providers in acquiring and interpreting ultrasound images. The research will start by exploring existing AI-assisted ultrasound technologies, identifying unmet operational needs and determining where further technological development could provide the greatest benefit to military healthcare.

Applications such as Extended Focused Assessment with Sonography in Trauma (EFAST), used to identify potentially life-threatening injuries, provide a relevant starting point. However, the research will also explore other promising applications of ultrasound and AI across military trauma care.

Beyond developing and evaluating AI algorithms, the project will investigate how these technologies can be effectively integrated into military medical practice, taking into account the capabilities of healthcare providers and the specific challenges of operational environments.

Although military healthcare is the primary focus, the resulting knowledge and technologies may also benefit civilian emergency care, including ambulance services and emergency departments.

Place of work

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 200 researchers are continuously striving to optimize healthcare. Close cooperation between preclinical researchers, radiologists and cardiologists gives a fantastic opportunity to implement new imaging techniques in clinical practice, and you will be working directly in this field.

Medical Ultrasound Imaging Center: MUSIC

The MUSIC laboratory works on the development, optimization, and clinical evaluation of new ultrasound imaging methods. For that, MUSIC collaborates with major vendors of ultrasound equipment. The focus of MUSIC is on AI-driven handheld ultrasound and development of high-end ultrasound solutions for improved diagnosis of breast cancer, carotid diseases, and liver steatosis.

AI-driven handheld ultrasound solutions are developed for improving diagnosis in low resource settings, and by general practitioners and doctors in child consultation centers. For that, the group has researchers with various backgrounds form engineering to medical doctors providing wide-ranging expertise in image reconstruction and processing, deep learning and other AI methods, and analysis, along with the design and performance of patient trials. The laboratory works closely with radiologists and industry.

You will be appointed as a PhD candidate at Radboudumc, which will be your primary place of work. The research will be conducted in collaboration with the Civil-Military Centre of Expertise for Trauma Care (CETC). The CETC is a civil-military partnership between the Netherlands Armed Forces and UMC Utrecht, dedicated to improving trauma care for both military personnel and civilians. Its ambition is to prevent avoidable deaths and minimise long-term disability following traumatic injuries. To achieve this, the CETC brings together scientific research, medical expertise, and the needs of military healthcare. Through this collaboration, you will also hold an appointment with the Ministry of Defense.

As part of this PhD project, you will work closely with researchers and clinical experts at Radboudumc, as well as healthcare professionals and researchers within the Ministry of Defense - CETC. This collaboration offers the opportunity to combine advanced scientific research with practical applications in military healthcare.

Profile

You are an analytical, curious and enthusiastic researcher who is motivated to conduct independent scientific research. You have a strong interest in translating technological innovations into clinical practice and enjoy working in multidisciplinary teams with researchers, physicians, engineers and other healthcare professionals.

In addition, you possess excellent communication skills and are proficient in English, both spoken and written. You are eager to contribute to innovative solutions that can improve trauma care in challenging operational environments.

• A Master's degree in Artificial Intelligence, Computer Science, Biomedical Engineering, Technical Medicine, or a related field.
• Experience with deep learning techniques and programming in Python or a comparable programming language.
• Affinity with medical (ultrasound) imaging and image analysis.
• An interest in military healthcare; previous experience within the Netherlands Armed Forces is considered an advantage.

Good to know

• The first job interviews will take place early december. Please take this into account.
• This position requires a Certificate of Conduct (VOG).

We are recruiting for this position ourselves. Unsolicited marketing is not appreciated, but do feel free to share the vacancy in your network!