Research Engineer - Procedural Geometry & Computational Modeling

Application Open:

Full-Time

MBZUAI is seeking a Procedural Geometry & Computational Modeling Research Engineer to support a Multiscale Biology Visualization AI project. The role focuses on designing and implementing algorithm-driven, deterministic geometry generators for subcellular structures, enabling biologically plausible and computationally efficient representations of cellular components. The Research Engineer will develop parameterized, testable shape synthesis pipelines that integrate upstream AI-generated biological outputs and produce standardized geometry assets for downstream visualization and rendering systems. The position requires strong expertise in computational geometry, structured algorithm design, and reproducible research practices within a fast-paced, interdisciplinary research environment.

Key Responsibilities

Procedural Geometry Modeling

• Design and implement procedural, algorithm-driven generators for subcellular geometry.
• Develop deterministic, seed-controlled, parameterized shape synthesis pipelines that are testable and reproducible.
• Create geometric representations for a broad set of cellular structures (target scope includes approximately 35 organelles).
• Balance biological plausibility, computational efficiency, and visual fidelity in geometry generation.

Pipeline Integration & Architecture

• Define schema- and configuration-driven interfaces to transform upstream biological AI model outputs into standardized geometry outputs.
• Prepare generated geometry for seamless integration into the visualization and rendering stack.
• Ensure interoperability across modeling, rendering, and AI-facing components.

Quality Assurance & Reproducibility

• Develop validation metrics and automated tests for topology correctness, realism, reproducibility, and performance.
• Contribute to code quality, structured documentation, and reproducible research practices.
• Maintain clear version control and collaborative development workflows.

Collaboration & Research Contribution

• Collaborate closely with visualization engineers, AI researchers, computational biologists, and modeling specialists.
• Participate actively in technical design discussions and solution development.
• Operate effectively in a fast-paced, agile research environment with evolving requirements.

Academic Qualifications Required

• Master’s degree in Computer Science, Computational Geometry, Computer Graphics, or a related field.
• A PhD in a relevant discipline will be preferred.

Professional Experience Required Essential:

• Demonstrated experience in computational geometry, mesh processing, procedural modeling, or simulation.
• Strong algorithmic skills with proficiency in Python (experience in C++, Rust, or Node.js is advantageous).
• Solid understanding of geometric data structures, topology, and polygonal mesh generation pipelines.
• Strong debugging skills and advanced algorithmic problem-solving ability.
• Experience working in collaborative development environments using tools such as Git and modern communication platforms.

Preferred:

• Experience with biological imaging, cellular morphology, or structural biology data.
• Knowledge of geometry libraries and polygonal mesh optimization for real-time or high-performance applications.
• Exposure to differentiable geometry or machine learning–guided geometry workflows.