• Position Title: Bioinformatician / PostDoc
• Project: Decoding Neurodegeneration at Single-Cell Resolution
• Location: [MBZUAI / Abu Dhabi, UAE]
• Position Type: Full-time, 2-3 years fixed-term contract
• Application Deadline: until filled

This project studies neurodegeneration at single-cell resolution, aiming to identify the cellular changes that drive disease and to detect them across the wider patient population. It combines unique, deeply characterised patient tissue, profiled with purpose-built assays, with the large public single-nucleus atlases of the human brain. Using advanced AI/ML methods, we will develop transfer-learning models that recover disease signatures in data where the underlying measurement was never made. This is a unique opportunity to work at the intersection of single-cell genomics, machine learning, and translational neuroscience.

Key Responsibilities:

• Process single-cell and single-nucleus RNA-seq data, from raw sequencing through to annotated cell atlases.
• Develop, benchmark, and validate machine-learning models that link cellular molecular states to disease status and clinical phenotype.
• Apply models to large public single-cell atlases and validate predictions against orthogonal evidence.
• Perform differential expression, cell-state, and pathway analyses, and interpret results in a disease context.
• Collaborate with an interdisciplinary team of experimental biologists, clinicians, and computational scientists.
• Document analysis pipelines, ensure reproducibility, and contribute to peer-reviewed publications.

Required Qualifications

• Master's degree or PhD in Bioinformatics, Computational Biology, Machine Learning, or a related field.
• Strong programming skills in Python and R.
• Experience with high-performance computing (HPC) environments and the Linux command line.
• Demonstrated experience with single-cell data formats and tools (Cell Ranger, Scanpy, Seurat).
• Knowledge of standard single-cell workflows
• Demonstrated experience building and evaluating machine-learning models on high-dimensional data
• Experience with deep learning frameworks (PyTorch, TensorFlow) and single-cell representation learning (e.g. scVI, transfer learning, single-cell foundation models).

Preferred Qualifications

• Experience with single-cell representation learning (e.g. scVI, transfer learning, single-cell foundation models).
• Familiarity with multi-omic or spatial single-cell data (snATAC-seq, spatial transcriptomics).
• Experience working with large public atlases (Human Cell Atlas, CELLxGENE, GTEx) and with harmonising heterogeneous cohorts.
• Experience in transcript-level or splicing analysis, or in long-read sequencing.
• Publication record in bioinformatics or machine learning.
• Ability to work independently and as part of a collaborative, multi-institutional team.

We Offer:

• Competitive salary and benefits package.
• Access to world-class datasets and computational resources.
• Opportunity to contribute to pioneering, high-impact research
• Collaborative and supportive research environment.

How to Apply:

Please submit your CV, a brief cover letter describing your relevant experience, and contact information for two references to alla.mikheenko@mbzuai.ac.ae with the subject line: Bioinformatician / Postdoc Application – [Your Name].

Review of applications will begin immediately and continue until the position is filled.