Postdoctoral Fellow- Computational Biology and Machine Learning

Tasks

• Advance machine learning methods for biological data
• Build single cell and spatial atlases
• Co lead publications and conference presentations
• Develop AI agents for hypothesis generation and experiment design
• Develop generative models for cell fate and perturbations
• Integrate imaging genomics and clinical data into unified representations
• Train foundation models for single cell biology

Perks/Benefits

• Hybrid working
• Mentorship culture
• Training workshops and career development

Skills/Tech-stack

Deep learning | Diffusion Models | Flow matching | Generative Modeling | Git | Machine Learning | Multiomics integration | PyTorch | Python | Reinforcement Learning | Representation Learning | SciPy | Scikit-learn | Single cell omics | Single-cell | Spatial transcriptomics | Statistical Techniques | TensorFlow | Transformers | Uncertainty Modeling