Chief Machine Learning Scientist in Biomedical Research
3 weeks ago
About the Role:
We are seeking a highly skilled Chief Machine Learning Scientist to join our interdisciplinary team at the Wellcome Sanger Institute. As a key member of our AI/ML Faculty group, you will play a critical role in advancing biological research through foundational models. Your primary focus will be on designing and developing innovative machine learning algorithms to analyze and interpret large-scale single-cell datasets.
Our team has access to unique data and substantial computational power, including GPUs, to train large models efficiently. You will work closely with Ph.D. students and postdocs to develop solutions for complex scientific problems in biology, providing supervision and training to junior team members.
Your responsibilities will include:
- Leading machine learning research projects and publishing outcomes in top-tier journals or conferences
- Collaborating with team members to propose, develop, and evaluate new machine learning models for single-cell data analysis and drug discovery
- Working with Ph.D. students and postdocs to develop solutions for interdisciplinary scientific problems in biology
- Contributing to writing scientific papers on biotechnology and biology
- Presenting research and analysis pipelines to internal and external audiences
Essential Skills:
Ph.D. or M.Sc. with equivalent research experience in a relevant quantitative discipline (e.g., Computer Science, Computational Biology, Genetics, Bioinformatics, Physics, Engineering, or Applied Statistics/Mathematics)
Previous ML work experience in a scientific/academic environment (RA/Internships considered as work experience)
Strong knowledge of Python, including core data science libraries such as Scikit-Learn, SciPy, TensorFlow, and PyTorch
Expertise in machine learning algorithms and frameworks, with experience in designing, training, and deploying ML models
Proficiency in handling and processing large datasets, including techniques for data cleaning, feature engineering, and data augmentation
Experience with high-performance computing environments, including the use of GPUs for training large-scale machine learning models
Estimated Salary: £65,000 - £85,000 per annum
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