PhD Deep learning approaches to improve application of transmission electron microscopy for characterizing nanoparticles in food and consumer products in the European regulatory framework

PhD Deep learning approaches to improve application of transmission electron microscopy for characterizing nanoparticles in food and consumer products in the European regulatory framework

Published Deadline Location
19 Jul 31 Jul Maastricht

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Are you interested in imaging, image analysis and computational methods? Do you want to apply advanced microscopy techniques? Would you like to use your skills in a societal relevant context? Then we would like to get to know you!

Job description

Nanotechnology is considered a key enabling technology by the European Commission. Individuals are exposed to nanotechnology based applications on a daily basis, including applications in food, textiles, personal protective equipment and medication. Despite its many advantages, the use of nanotechnology can bring health risks that need to be carefully assessed and controlled in line with the European Union’s regulatory framework. To investigate public health concerns without hampering fast innovation, methods that speed up the physicochemical characterization of nanomaterials need to be developed.

This PhD project will combine electron microscopy (EM)-based imaging with advanced image analysis routines to identify and characterize nanomaterials in food and consumer products in a timely and automated manner, building on existing and novel machine learning, algorithms for image analysis, and particularly on deep learning algorithms; data analysis and automation.

The PhD project will improve sample throughput, cost efficiency, scalability, digitalization and availability of standardized methods for regulatory purposes and risk assessment of nanomaterials. The methods are developed specifically in a health related context, and span over application areas in food, environment, textiles, medicine, and general consumer goods.



Maastricht University (UM)


Minimum Qualifications:

  • You have a Master’s degree in mathematics, physics, computer science, bio-informatics, engineering, or in a related field with evidence of interest in image analysis and computational methods;
  • As a successful candidate, you will have strong quantitative skills in data assessment, programming, and machine learning/statistical methods
  • You are curious and thrive in a multi-disciplinary environment and enjoy working together with other researchers of different backgrounds.   

Desired Qualifications:

  • Experience with image analysis,
  • Experience with electron microscopy techniques,
  • Acquainted with working in a quality system

Generic competencies:

  • Good academic writing skills
  • Excellent spoken and written English
  • Excellent communicative skills

Conditions of employment

Fixed-term contract: 4 years.

  • We offer a rewarding career at a young university in the heart of Europe, with a distinct global perspective and a strong focus on innovative research and education, embedded in a strong team and excellent consortium;           
  • The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO), supplement with local UM provisions. For more information on terms of employment, please visit our website > About UM > Working at UM;           
  • The salary will be set in the PhD-candidate salary scale of the Collective Labor Agreement for Dutch Universities (€ 2.541 gross per month in the first year up to € 3.247 gross per month in the fourth year). On top of this, there is an 8% holiday allowance and a 8.3% year-end allowance;           
  • We offer an attractive package of fringe benefits such as reduction on collective health insurance, substantial leave arrangements, optional model for designing a personalized benefits package and application for attractive fiscal arrangements for employees from abroad.

We offer a full-time employment contract as a PhD candidate for 4 years.

Teaching will be expected for 20 % of the time. Research will be required at the two venues, both Maastricht University and Sciensano (Uccle, Belgium).


Maastricht University (Data Analytics and Digitalisation) / Sciensano Belgium

The project is an interdisciplinary project of the groups “Data Analytics and Digitalization” (School of Business and Economics, Maastricht University) and “Trace Elements and Nanomaterials” (Chemical and Physical Health Risks, Sciensano, Belgium).

Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. The School of Business and Economics is the youngest economics and business faculty in the Netherlands with a distinctively international profile. It belongs to the 1% of business schools worldwide to be triple-crown accredited (EQUIS, AACSB and AMBA). SBE strongly believes in close connections with its academic partners and societal stakeholders, with its students and alumni, and with businesses and organizations in the Limburg Euregion, the Netherlands, Europe and the rest of the world.

The department of Data Analytics and Digitalisation (DAD) connects data science (mathematics, statistics, computer science, artificial intelligence) with business and economics research (finance, accounting, marketing, information management, operations, micro- and macroeconomics, policy design). We are responsible for conducting top-level research in data science for business and economics ranging from fundamental theoretical studies to applied industrial projects.

Sciensano is a Belgian public health institution where science and health are central to its mission. Sciensano’s strength and uniqueness lie within the holistic and multidisciplinary approach to health. More particularly we focus on the close and indissoluble interconnection between human and animal health and their environment (the “One health” concept). By combining different research perspectives within this framework, Sciensano contributes in its unique way to everybody’s health. For this, Sciensano builds on the more than 100 years of scientific expertise of the former Veterinary and Agrochemical Research Centre (CODA-CERVA) and the ex-Scientific Institute of Public Health (WIV-ISP).

The research group Trace Elements and Nanomaterials has a long standing experience in the study of trace elements and nanoparticles in food, feed, food supplements and materials in contact with food. For these topics, it functions as the Belgian National Reference Laboratory (NRL). The group participated in many national and international expert groups and research projects focusing on the physicochemical characterization of nanomaterials by electron microscopy in a regulatory context.


  • PhD
  • AT2022.297


Maastricht University (UM)

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