Application Open:
Full-Time
MBZUAI is seeking a highly qualified Research Scientist to support the development and scientific advancement of AI-driven models that predict and simulate cellular state changes in response to molecular perturbations by small-molecule compounds, peptides, proteins, genetic edits, and RNA-based interventions. These predictive models are essential for target identification, drug screening, precision cell engineering, and high-throughput discovery workflows. The Research Scientist will work closely with Research Engineers, faculty, and experimental collaborators to design biological modeling strategies, validate model outcomes, and assess publication, intellectual property (IP), and scientific dissemination opportunities. The role ensures timely scientific delivery and will prepare structured progress reports for the Principal Investigator (PI).
Key Responsibilities
Scientific Project Advancement
- Support the scientific design, hypothesis formulation, and analysis to guide AI model development for cellular response prediction and simulation.
- Work collaboratively with Research Scientist to validate model outputs, interpret biological relevance, and ensure methodological rigor.
- Evaluate and integrate cutting-edge scientific literature, benchmarking methods, and emerging data modalities relevant to the project.
- Identify new experimental directions, technical improvements, or data sources that strengthen the project’s scientific foundation.
Develop high-quality 2D/3D visualizations of generative model results in molecular and cellular levels
- Collaborate with scientists and researchers to understand biological concepts, data requirements, and visualization needs, ensuring scientific accuracy in all visual outputs.
- Design interactive visualization tools or dashboards that help researchers explore molecular and cellular generative models in real time.
- Produce educational and presentation materials, including figures, animations, and explainer videos for publications, grant proposals, conferences, and outreach.
- Ensure visualizations adhere to scientific accuracy while meeting aesthetic and communication standards for diverse audiences (scientific, clinical, public).
- Optimize visualizations for performance in interactive environments, VR/AR applications, or large-scale displays.
Project Management & Reporting
- Track scientific milestones, risks, and deliverables in alignment with internal project timelines.
- Prepare structured scientific reports, dashboards, and update summaries for regular review by the PI.
- Ensure that scientific progress meets institutional expectations for research excellence, rigor, and timely delivery.
Collaboration & Knowledge Transfer
- Work closely with faculty, postdoctoral fellows, research engineers, and external partners to maintain scientific alignment across collaborative activities.
- Provide mentorship and technical guidance to Research Engineers and student researchers involved in the project.
- Contribute to internal workshops, discussions, and seminars to foster cross-team knowledge exchange.
Research Output Development (Publications & Patents)
- Assess publication opportunities and lead manuscript preparation for high-impact journals and conferences.
- Work with the Technology Transfer Office (TTO) to evaluate patentability of novel algorithms, biological insights, or modeling frameworks.
- Ensure all scientific communication adheres to MBZUAI’s standards for confidentiality, research integrity, and compliance.
Operational & Institutional Alignment
- Ensure that scientific activities are conducted in compliance with MBZUAI research governance standards, ethical requirements, and relevant HR & operational policies.
- Contribute to resource planning by identifying scientific needs, data requirements, and infrastructure dependencies.
- Maintain comprehensive documentation of experiments, data workflows, and scientific methods to support reproducibility and institutional review.
Other Duties
- Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.
Academic Qualification Required
- PhD in Computational Biology, Bioinformatics, Machine Learning for Biology, Systems Biology, Biomedical Engineering, or a related field.
Professional Experience Required
Essential:
- Minimum 2 years postdoctoral research experience.
- Strong research background in applying machine learning or deep learning to biological data.
- Experience working with multi-omics datasets (transcriptomics, proteomics, CRISPR screens, perturbation assays).
- Demonstrated ability to publish in reputable peer-reviewed journals.
- Proficiency in scientific computing (Python, PyTorch/TensorFlow, statistical analysis).
- Proven ability to interpret biological systems and link molecular perturbations to phenotypic outcomes.
Preferred:
- Experience working with single-cell data, large-scale perturbation datasets, or foundation models for biology.
- Background in computational drug discovery, gene regulatory modeling, or systems pharmacology.
- Familiarity with high-performance computing, MLOps workflows, and large-scale machine learning pipelines.
- Experience with drafting or contributing to patents or technical disclosures.
