Postdoc Structural Biology of the Neuronal Synapse

We seek an ambitious Computational Structural Biologist (PhD) specializing in cryo-electron tomography and machine learning, to unravel the molecular recognition code of neuronal synapes.

Job description
A 2.5-year position is available for a postdoctoral fellow in the research group of Dimphna Meijer, Department of Bionanoscience, Delft University of Technology, the Netherlands.

The long-term goal of our research is to understand synapse assembly and disassembly at the molecular level, during health and disease. We address questions such as: What is the underlying structural basis of synapse formation? What happens at the nanoscale in a diseased brain? We have recently determined several cryo-EM structures of synaptic cell adhesion molecules that together reveal part of a molecular recognition code.

Join our interdisciplinary lab to drive novel cryo-ET data analysis. You will develop and apply advanced computational methods to visualize cellular structures at the molecular level, bridging biology and data science. This role leverages your background in structural biochemistry, image processing, and software engineering. You’ll work closely with experimentalists to interpret tomographic data, integrate spatial constraints, and publish methods and results. Our environment values open science and teamwork, and you will contribute to open-source tools and collaborate across discipline.

Responsibilities:

• Pipeline Engineering: Build and maintain robust, documented software pipelines for tomogram processing (leveraging Python/C++ and HPC/GPU resources) and co-develop open-source tools.
• Data Analysis & Visualization: Perform quantitative analysis of 3D cellular data (e.g. spatial distribution of complexes) and interpret results to advance biological insights. Create informative visualizations and reports for collaborators and publications.
• Algorithm Development and Structure Determination: Design, implement, and optimize algorithms for detecting, localizing and reconstructing macromolecules in cryo-ET tomograms (e.g. using template matching, GPU-accelerated search, and machine learning).
• Collaboration & Communication: Work in a multidisciplinary team (cell biology, biophysics, and computing) to integrate structural data with other modalities. Mentor students or interns on computational projects. Present findings at team meetings and scientific conferences.
• Stay Current: Keep abreast of advances in cryo-EM/ET, image analysis, and AI-driven structural biology. Adopt best practices in open science (sharing code, reproducibility) and help drive innovation in the field.

Job requirements
We are looking for a highly motivated and goal-oriented researcher that is willing to take on new challenges. The candidate has a PhD. degree in structural biology, computer sciences or related field.

Required Qualifications:

• Strong computational skills: Expertise in Python and C/C++ programming, numerical libraries (e.g. NumPy, SciPy), and parallel computing (GPU/HPC). Experience developing and deploying scientific software.
• Cryo-ET/Image Analysis experience: Hands-on experience with electron tomography or related structural imaging, including image simulation or analysis (e.g. template matching in tomograms).
• Machine learning knowledge: Familiarity with ML frameworks (e.g. TensorFlow/PyTorch) and implementing deep-learning methods for image data.
• Track record of research: Published peer-reviewed articles in structural biology or computational imaging. Demonstrated problem-solving and algorithm development skills.

Preferred Qualifications:

• Postdoctoral research or relevant industry experience in computational structural biology.
• Experience with specific cryo-EM software (e.g. RELION, Warp) or bioinformatics tools for macromolecular modeling (e.g. AlphaFold, ChimeraX).
• Familiarity with Linux environments, Git, and open-source collaboration

TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Applied Sciences
With more than 1,100 employees, including 150 pioneering principal investigators, as well as a population of about 3,600 passionate students, the Faculty of Applied Sciences is an inspiring scientific ecosystem. Focusing on key enabling technologies, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we educate innovative students in broad Bachelor's and specialist Master's programmes with a strong research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science & Technology, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers.

Click here to go to the website of the Faculty of Applied Sciences.

Conditions of employment

• Duration of contract is 2,5 years Temporary
• A job of 38-40 hours per week.
• Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands. .

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Dimphna Meijer, Principal Investigator, e-mail: D.H.M.Meijer@tudelft.nl.

Application procedure
Are you interested in this vacancy? Please apply no later than 9 March 2026 via the application button and upload the following documents:

• Letter of motivation (generic letters will be disregarded)
• Detailed CV

You can address your application to Dr. Dimphna Meijer, Principal Investigator.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.