Postdoc Structural Biology Neuronal Synapse

Offer Description

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

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.

• 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.

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.

• Strong computational skills:
  Expertise in Python and C/C++ programming, numerical libraries (e.g. Num Py, Sci Py), 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. Tensor Flow/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.

• Post‑doctoral 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. Alpha Fold, Chimera
  
  X).
• Familiarity with Linux environments, Git, and open‑source collaboration

• Duration of contract: 2.5 years (temporary)
• Work hours:
  
  38‑40 hours per week.
• Salary and benefits in accordance with the Collective Labour Agreement for Dutch Universities.
• Excellent pension scheme via the ABP.
• Possibility to compile an individual…