PhD-candidate position on Radiomics-based interpretable Artificial Intelligence within a European project

Updated: about 2 months ago
Deadline: 06 Sep 2020

PhD-candidate position on Radiomics-based interpretable Artificial Intelligence within a European project
PhD-candidate position on Radiomics-based interpretable Artificial Intelligence within a European project
Published Deadline Location
21 Aug 6 Sep Maastricht

We are looking for a highly motivated and talented PhD student to develop and validate imaging-based clinically relevant, interpretable and interoperable artificial intelligence models for radiological imaging within a large European project.
Job description

This PhD project takes place within the department of Precision medicine ( ) research institute GROW at the Faculty of Health, Medicine, and Life Sciences of Maastricht University.

In this project, you will extract quantitative features from high quality clinical imaging data sets (PET/CT/MR) to ultimately serve as imaging biomarkers to correlate to pathology, molecular biomarkers and to predict diagnosis. Your research will involve utilizing a high-throughput image characterization workflow and relating quantitative image features to pathology and diagnosis using a so-called “Deep-Learning and radiomics” approaches available in open source or in commercial environment. You are going to analyze existing annotated datasets of medical images with Deep Learning and radiomics solutions available open source or in commercial environment. You time will be dedicated to analysis of the literature & discussion with clinicians, curation of data, training with the Deep Learning-radiomics technique, features extraction of the images, statistical analysis and correlation with the endpoint (clinical diagnosis, pathology and molecular endpoints), creating new solutions and finally writing and discussion of your results.

This project is funded by the European commission within a lively and diverse consortium EuCanImage.


  • max. 38 hours per week
  • €2395—€3061 per month
  • Maastricht View on Google Maps

Maastricht University (UM)


We are looking for applicants who have completed a Master in (bio)medical engineering, technical medicine, physics, machine learning, computer science, biomedical sciences or equivalent, with an interest for quantitative imaging, Deep Learning and “Radiomics”.

Additional requirements:

  • Experience with modelling techniques/machine learning techniques
  • Experience in deep learning, either using TensorFlow (Keras) or PyTorch
  • Preferably experience with imaging techniques (CT, MRI, PET), DICOM and image analysis
  • Programming experience, preferably a scripting language such as Python or R
  • Familiarity with relational database systems (SQL) preferred.
  • Fluently in English, both writing and speaking
  • An independent and practical personality and you are able to take initiatives.
  • We are looking for a positively minded scientist motivated to learn new approaches and ready to work hard to build a scientific career. The candidate should have a sociable personality with good communication skills, a problem-solving attitude, learn fast to plan his own workload effectively and to delegate when necessary and have conceptual ability.


Conditions of employment

Fixed-term contract: 4 years.

The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website > Support > UM employees.

The full-time position is offered for four years (first year + three years after receiving a positive evaluation), with a yearly evaluation. The salary will be set in PhD salary scale of the Collective Labor Agreement of the Dutch Universities (€ 2.395,- gross per month in first year to € 3.061,- last year). On top of this, there is an 8% holiday and an 8.3% year-end allowance. Employees relocating from abroad may be eligible for the Dutch ‘30% ruling’, a tax advantage which results in a significantly higher net salary.

GROW-School for Oncology and Developmental Biology

The School for Oncology & Developmental Biology (GROW) focuses on research and teaching of genetic and cellular mechanisms, as well as environmental and life-style factors that underlie normal (embryonic and fetal) and abnormal (cancer) development. The emphasis is on basic and translational research, aiming at innovative approaches for individualizing prevention, patient diagnosis, and treatment for genetically determined diseases and cancer.

Department of Precision Medicine

In the Department of Precision Medicine we believe that Sciences will make progress by integrating different scientific sub-discipline: the convergence sciences concept: integration of biology clinical sciences and technology. (Visit ). Our objective is to offer a stimulating environment with modern and advanced research facilities in an innovative field for a young and motivated scientific researcher.  Our group has an excellent international reputation and, for example, over recent years has published 6 papers in journals within the “Nature” group. Our alumni have an impressive track-record of high profile positions in the academic world (Europe, USA, Asia..), start-ups and industry.


Additional information

Additional information about the vacancy can be obtained from dr. Avishek Chatterjee ( ) and dr. Henry Woodruff ( ).
Interested candidates should send a letter of motivation, a detailed CV and the contact details of two referents to:   

Please mention also the vacancy number/Job number (AT2020.250) and/or the project name in your application.

Application procedure

Maastricht University is committed to nurturing an inclusive culture and a welcoming atmosphere. This inclusiveness strategy has resulted in a very diverse representation of nationalities and cultures. We strongly believe that diversity (including, but not limited to nationality, age and gender) of the staff and student population will increase the quality of UM education & research. Fostering diversity and inclusivity creates an academic community where individual talents thrive, and values and differences are cherished. We strongly encourage you to apply if you are qualified for this position.

Apply via postal mail
Apply via postal mail

Don't forget to mention AcademicTransfer and the job number: AT2020.250 in your letter.

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