Your role

Develop, implement and optimize innovative microscopy, cytometry and image analysis workflows to support cutting-edge biomedical research

Design, maintain and continuously improve reproducible image and cytometry data analysis pipelines using state-of-the-art open-source and commercial software

Evaluate, validate and implement emerging imaging technologies, image analysis methods and computational workflows, including AI-based approaches

Collaborate closely with researchers to design microscopy and cytometry experiments and develop tailored solutions for complex biological questions

Provide scientific expertise in microscopy, cytometry, quantitative image analysis and experimental design

Contribute to the evaluation, validation and implementation of new instrumentation, software solutions and quality assurance procedures within the Bioimaging Platform

Develop, maintain and disseminate standard operating procedures (SOPs), best practice guidelines and quality control protocols

Ensure the maintenance, documentation and continuous optimization of computational tools and analysis workflows deployed by the platform

Contribute to collaborative research projects, scientific publications and competitive grant applications

Deliver advanced training courses, workshops and scientific consultations on microscopy, cytometry and quantitative image analysis

Contribute to the continuous innovation and scientific excellence of the Bioimaging Platform

Your profile

A University Master's degree (or officially recognized equivalent diploma) in biology, biomedical engineering, biophysics, bioinformatics, computer science, physics, engineering, or a related discipline
Proven experience with advanced light microscopy and/or flow cytometry, including quantitative image and/or cytometry data analysis
Experience developing and implementing quantitative image analysis workflows using open-source platforms
Programming skills in Python, MATLAB, or another scientific programming language
Excellent command of English is required

Preferred but not mandatory:

Experience applying deep learning or AI-based methods for image segmentation, object detection, classification or quantitative bioimage analysis
Experience with confocal, live-cell, high-content, super-resolution or light-sheet microscopy
Experience with FlowJo and other cytometry data analysis software
Experience developing automated and reproducible image analysis workflows
Knowledge of image data management and FAIR data principles
Experience contributing to collaborative research projects, scientific publications and competitive grant applications
Experience working in a research infrastructure, core facility or interdisciplinary research environment

We offer

A modern, dynamic university with a personal and inclusive atmosphere. Multilingual and international character. Staff coming from more than 90 countries. Member of The Guild of European Research Intensive Universities

An exceptional research environment, supported by skilled staff and high-quality equipment. Strong links to professional sectors and the Luxembourg labour market. A unique urban campus with excellent infrastructure

A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and a wide range of non-academic partners including ministries, local governments, associations, and NGOs

How to apply

Applications should include:

Curriculum Vitae
Cover letter

Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.

General information:

Contract Type: Fixed Term Contract 36 Month
Work Hours: Full Time 40.0 Hours per Week
Location: Belval Campus
Internal Title: Research and development specialist
Job Reference: UOL08503