Postdoc Scientist: CryoSTEM Foundation Models Architect

Mohamed bin Zayed University of Artificial Intelligence; Abu Dhabi; On-site; AED 240,000 - 360,000; Full time

Benefits offered by this job

Comprehensive health & life insurance

Relocation support for international-h

Live in Abu Dhabi

Job summary

MBZUAI seeks a highly motivated Postdoctoral Research Associate to join an interdisciplinary project on cryoSTEM foundation models. You will understand cryoSTEM physics, design novel model architectures, and implement parallel systems for training across multi-GPU clusters on multi-terabyte datasets.

The role includes mentoring graduate students, leading sub-projects, and publishing high-impact findings to advance computational biology and machine learning.

Qualifications

• PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Biomedical Imaging or related field.
• Strong publication record in computational microscopy, computer vision or parallel ML.
• Adaptability to bridge computational microscopy, computer vision or parallel ML.
• Experience with biomedical imaging, especially electron microscopy data, is highly preferred.
• Excellent analytical, oral, and written communication skills.

Responsibilities

• Understand CryoSTEM microscopy physics and operation.
• Design foundation models for cryoSTEM data and data pipelines.
• Deploy parallel computing systems for training large-scale cryoSTEM models.
• Lead complex research sub-projects and meet milestones.
• Mentor graduate students and junior researchers.
• Publish high-impact scholarly articles and share findings.

Skills

CryoSTEM microscopy

Parallel ML

Distributed systems

Computer vision

Biomedical imaging

Education

PhD in CS/EE/AI/Biomedical imaging

Tools

PyTorch

TensorFlow

CUDA

Job description

MBZUAI seeks a highly motivated Postdoctoral Research Associate to join an interdisciplinary project on cryoSTEM foundation models. You will understand cryoSTEM physics, design novel model architectures, and implement parallel systems for training across multi-GPU clusters on multi-terabyte datasets.

The role includes mentoring graduate students, leading sub-projects, and publishing high-impact findings to advance computational biology and machine learning.