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.
