Postdoctoral Research Associate

implement parallel systems capable of training such models across large GPU clusters on cryoSTEM datasets in the multi-terabyte range. This position plays a pivotal role in supporting ongoing, high-impact research programs within our lab.

The successful candidate will be working under the joint guidance of two experts in computational microscopy and machine learning systems, blending expertise in advanced bioimage informatics and parallel computing:

• Dr. Min Xu – Affiliated Associate Professor of Computer Vision, MBZUAI & Associate Professor, Carnegie Mellon University. Dr. Xu directs a dynamic research laboratory focused on computational biology, bioimage informatics, and structural biology. His core scientific research uses computer vision to pioneer new methods for 3D cellular structure analysis and cryo-electron tomography (cryo-ET).
• Dr. Qirong Ho – Assistant Professor of Machine Learning and Computer Science, MBZUAI. Dr. Ho specializes in distributed machine learning and systems architecture. His expertise drives the design of robust, parallelized systems required to scale massive biomedical imaging models efficiently over distributed GPU environments.

Key Responsibilities

• Understand CryoSTEM Microscopy: Become deeply familiar with the physics and operation of state-of-the-art cryoSTEM microscopes.
• Design Foundation Models: Create new model architectures for cryoSTEM data, which will be informed by the strengths and limitations of cryoSTEM microscopes and their data pipeline. These foundation models will be used to improve the operation of cryoSTEM microscopes when applied to biological samples.
• Parallel Model Training: Deploy parallel computing systems for training large-scale cryoSTEM foundation models.
• Project Leadership: Manage complex research sub-projects and ensure research milestones are met.
• Mentorship: Guide and mentor graduate students and junior researchers within the lab.
• Academic Output: Author high-impact publications and produce other key deliverables to share findings with the broader scientific community.

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is a world-leading university dedicated to advancing AI as a global force for good. The UAE’s visionary leaders established MBZUAI to educate and develop top talent, conduct advanced research, foster an innovation ecosystem, and act as a strategic think tank for the public and private sectors.

The University attracts world-class thinkers and doers in computer science, AI, bioscience, humanities and beyond. Our groundbreaking academic research initiatives are working on developing future solutions that will impact the world and change the way we imagine things.

Why Join MBZUAI?

• Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions
• Exceptional Benefits:
  • Comprehensive health & life insurance
  • Relocation support for international hires
• Live in Abu Dhabi: World’s safest city, year-round sunshine, rich culture, and modern amenities
• Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers

Qualifications

This position requires a PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Biomedical Imaging, Computational Biology, or a closely related field.

• Research Record: A strong, established track record of publications in computational microscopy, computer vision, or parallel machine learning
• Adaptability: A demonstrated, strong willingness to learn and bridge the gap into complementary domains required by this project (computational microscopy, computer vision or parallel ML).
• Domain Knowledge: Experience working with biomedical imaging is highly preferred, with a particular emphasis on electron microscopy (EM) data.
• Communication: Excellent analytical, oral, and written communication skills.

Application Instructions

To apply for this position, please submit the following items:

• A comprehensive CV, including a complete list of publications.
• A research proposal based on the following microscopy publication: Shadow montage and cone-beam reconstruction in 4D-STEM tomography. Microscopy and Microanalysis. 2026.
• Contact information for three professional references.
• Name and contact details for three referees (Referees will be contacted during the recruitment process to upload their reference letter via Interfolio)