PhD candidate - Medical image analysis and AI in hemostasis reseach

Official university vacancy imported from Maastricht University. Details are presented for discovery and may change. Confirm the latest requirements and apply on the official source.

• Our goal: to develop an automated, high-throughput analysis pipeline for flow chamber images using artificial intelligence. By doing so, we aim to accelerate, standardize, and further improve the analysis of thrombus formation under flow conditions for both scientific research and future clinical applications. The generated data will be used to study clinically relevant hemostatic phenotypes, treatment effects, and the potential value of flow chamber testing in patients with bleeding disorders.
• Your colleagues: you will become part of the Department of Biochemistry within the Faculty of Health, Medicine and Life Sciences (FHML), the Cardiovascular Research Institute Maastricht (CARIM), and work closely with the Central Diagnostic Laboratory (CDL) of Maastricht UMC+. You will join a multidisciplinary team of researchers, laboratory analysts, clinical chemists, hematologists, data scientists, and IT specialists.
• Analyze the current (semi-)automated image and data analysis workflow of the Maastricht Flow Chamber and identify opportunities for improvement.
• Develop AI models for the automated segmentation, quantification, and classification of flow chamber images, using deep learning and self-supervised techniques that also leverage unlabeled data.
• Automate the processing and analysis of large datasets generated from flow chamber experiments.
• Validate the developed AI models and translate them into a robust high-throughput analysis method that aligns with clinical questions in hematology, such as the diagnosis of unexplained bleeding and clotting disorders.
• Depending on the progress of the project, apply similar data science and AI methods to other complex laboratory datasets in the field of hemostasis and thrombosis.
• Collaborate closely with laboratory researchers, clinicians, and data scientists to integrate imaging results with clinical and laboratory data and help translate these findings into clinically relevant conclusions.
• Present your findings at national and international conferences and publish your work in leading international scientific journals.
• You hold a completed Master's degree, preferably in biomedical engineering, biomedical sciences, medicine, systems biology, clinical health sciences, (clinical) data science, bioinformatics, or a related discipline.
• You have a demonstrated affinity for data analysis and programming (e.g. Python or R), e.g. via projects, internships or other work experience where you’ve analysed datasets. Experience with machine learning, deep learning (e.g. scikit-learn, TensorFlow or PyTorch), or medical image analysis (e.g. segmentation or classification) is considered a strong advantage.
• You have a clear interest in hemostasis, thrombosis, and laboratory medicine, and understand that successful AI solutions start with a thorough understanding of the underlying clinical problem. Prior experience in these fields is not required, but you should be motivated to develop the necessary biological and clinical understanding.
• You possess excellent communication skills in English, written and spoken. Proficiency in Dutch is a strong advantage.
• You are independent, curious, and proactive, while also enjoying working in multidisciplinary teams with researchers, clinical chemists, medical specialists, IT professionals, and other healthcare professionals.
• A one-year employment contract (1.0 FTE), which will be extended by three additional years upon satisfactory performance.
• A gross monthly salary between € 3.204 en € 4.051 (based on full-time employment of 38 hours per week). 8% holiday allowance and an 8.3% year-end bonus.
• 29 vacation days (based on full-time), four additional days off (Carnival Monday and Tuesday, Good Friday, and Liberation Day), and the possibility to accrue up to 12 extra days through compensation hours.
• Flexible working hours, a home office allowance, and the option to work from home.
• Freedom and space to shape your work independently and develop your ideas.
• A close-knit community of colleagues to collaborate and grow with.
• A solid pension plan via ABP, company fitness schemes, and access to various university sports facilities.
• An inspiring work environment in the heart of Europe.
• A brief motivation letter
• Your academic transcript