Three-year PhD position in machine learning and deep learning with medical applications and alg[...]

University of Antwerp; Marseille; Sur place; EUR 60 000 - 80 000; Plein temps

Résumé du poste

An exciting PhD opportunity at the intersection of computer science and medicine awaits at a leading university. The candidate will focus on machine learning applications in dermatology and contribute to innovative research aimed at improving automated diagnoses of skin lesions, supported by expert guidance from clinical dermatologists.

Prestations

Stimulating scientific environment

Interdisciplinary research support

Qualifications

• Master’s 2 degree in Computer Science, Applied Mathematics, Data science, or a related field required.
• Solid programming skills in Python, experience with AI/ML libraries.
• Interest in clinical applications and good communication skills.

Responsabilités

• Develop algorithms for extracting features from 3D VECTRA images.
• Conduct clinical evaluations and performance assessments.
• Create algorithmic frameworks using concept-driven methodology.

Connaissances

Programming skills in Python

Machine learning

Explainable AI (XAI)

Unsupervised learning

Dimensionality reduction

Analytical and critical thinking

Good communication

Formation

Master’s 2 degree in Computer Science or related field

Description du poste

Three-year PhD position in machine learning and deep learning with medical applications and algorithms interpretability (funded by Amidex)

RESEARCHER PROFILE:PhD/ R1: First stage Researcher
RESEARCH FIELD(S)1:Computer science – Medicine - Medical imaging
MAIN SUB RESEARCH FIELD OR DISCIPLINES1: Computer science – Medicine - Medical imaging – Data science- IA- Dermatology- Onco-dermatology- Skin cancers

JOB /OFFER DESCRIPTION

This PhD project is part of an interdisciplinary collaboration between computer science researchers and clinical/research dermatology teams.

Building on our previous research based on dermatological concept modeling automated detection systems of melanoma, this PhD project is based on the hypothesis that analyzing all skin lesions of an individual — made possible through full-body 3D imaging using the VECTRA system — will allow us to improve and personalized automated diagnosis of melanoma and also enrich existing dermatological concepts and define new ones and enrich the dataset. This would help narrow the gap between algorithmic analysis and the clinical reasoning used by dermatologists when diagnosing melanoma in front of a real patient.

Its primary goal is to deepen the modeling of dermatological concepts by leveraging prior research and incorporating new concepts defined by expert dermatologists. The candidate will work on identifying and formalizing clinically relevant dermatological features for melanoma detection, and on developing algorithms capable of automatically extracting these new features from 3D VECTRA images. These features will then be used to mimick the dermatologist’s diagnostic decision-making process.By mimicking the reasoning strategies of clinicians, the system will provide a transparent and medically relevant decision-support tool, bridging the gap between machine learning outputs and clinical interpretation and clinical fitting of this system.

Practically during the PhD, the candidate will design algorithmic frameworks based on a concept-driven methodology inspired by dermatologists’ global cognitive analysis. He will develop models that automatically extract distinctive and interpretable features, validated through expert clinical analysis. The work will include exploring optimization techniques such as low-rank matrix approximation and learning in unsupervised settings. The candidate will use explainable AI tools to improve interpretability of the results. The candidate will also conduct clinical evaluations and performance assessments of the developed models using real-world case studies, working closely with dermatologists for joint analysis and validation of results.

TYPE OF CONTRACT:TEMPORARY
JOB STATUS:FULL TIME
APPLICATION DEADLINE:15/07/2025
ENVISAGED STARTING DATE:01/11/2025
ENVISAGED DURATION: 36 months
JOB NOT FUNDED THROUGH AN EU RESEARCH FRAMEWORK PROGRAMME

WHAT WE OFFER:

This interdisciplinary PhD project provides a unique opportunity to work at the interface of computer science and medicine (dermatology). The candidate will benefit from a stimulating scientific environment, combining cutting-edge research in artificial intelligence and computer vision with clinical expertise in dermatology. Throughout the thesis, the student will be supported by both computer scientists and researcher dermatologists, ensuring strong guidance for the development of clinically relevant AI applications in dermatology based on innovative and relevant dermatological concepts.The net monthly salary for this PhD position is estimated to be approximately €1,800.

Additional information: The Euraxess Center of Aix-Marseille Université informs foreign visiting professors, researchers, postdoc and PhD candidates about the administrative steps to be undertaken prior to arrival at AMU and the various practical formalities to be completed once in France: visas and entry requirements, insurance, help finding accommodation, support in opening a bank account, etc. More information onAMU EURAXESS Portal

QUALIFICATIONS, REQUIRED RESEARCH FIELDS, REQUIRED EDUCATION LEVEL, PROFESSIONAL SKILLS, OTHER RESEARCH REQUIREMENTS

We are seeking a highly motivated and curious PhD candidate with a strong interest in interdisciplinary research at the intersection of computer science and medical imaging in dermatology.

The candidate will have:

• A Master’s 2 degree (or equivalent) in Computer Science, Applied Mathematics, Data science, or a related field.
• Solid programming skills, particularly in Python (experience with AI/ML libraries such as PyTorch, TensorFlow, scikit-learn).
• A background in machine learning with an interest in explainable AI (XAI) or concept-based approaches.
• Experience with unsupervised learning, dimensionality reduction, or latent space exploration methods (e.g., clustering, t-SNE, UMAP, autoencoders) would be considered a strong asset.
• Excellent oral and written communication skills in Englishare required. French is a plus but not mandatory.
• An interest in clinical applications and the ability to interact with medical professionals

Soft skills:Autonomy, Teamwork, Analytical and critical thinking, Adaptability, Co-operation,Pro-activity, Innovative, good communication, A desire to contribute to meaningful, translational research with real-world impact in healthcare.

REQUESTED DOCUMENTS OF APPLICATION, ELIGIBILITY CRITERIA, SELECTION PROCESS

• CV
• Master’s‐level academic transcript (with grades)
• Reference letters(preferably two) or contact information of referees.
• Copy of diplomas(with certified translations if not in English or French).

Selected candidates will be interviewed remotely. The interview will include a presentation of previous work and a discussion of the project’s context.

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Job details

Title

Three-year PhD position in machine learning and deep learning with medical applications and algorithms interpretability (funded by Amidex)

Published

2025-06-30

2025-07-15 23:59 (Europe/Paris)
2025-07-15 23:59 (CET)

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