Staff Machine Learning Scientist

We are seeking a Staff Machine Learning Scientist to join our Machine Learning Science team within the Computational Science department. As a Staff Machine Learning Scientist, you will play a key role in developing algorithms for early, blood-based detection tests for cancer. You will build on a foundation of machine learning and deep learning skills to develop models for identifying molecular signals from blood.

Responsibilities:

• Independently pursue cutting-edge research in AI applied to biological problems, including cancer research, genomics, and computational biology.
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
• Develop models that achieve high accuracy and generalise robustly to new data.
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model.
• Collaborate with ML Engineering partners to ensure that our computational infrastructure supports optimal model training and iteration.
• Work closely with cross-functional teams, including computational biologists, molecular biologists, and ML engineers.

Requirements:

• PhD or equivalent research experience with an AI emphasis in a relevant, quantitative field.
• 6+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise in driving independent research in applied machine learning, deep learning, and complex data modeling.
• Practical and theoretical understanding of fundamental ML models, including generalised linear models, kernel machines, decision trees and forests, neural networks, boosting, and model aggregation.
• Practical and theoretical understanding of DL models, including large language models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in a general-purpose programming language, such as Python, R, Java, C, or C++.
• Proficient in one or more ML frameworks, such as PyTorch, TensorFlow, or JAX.
• Experience with ML analysis and developer tools like TensorBoard, MLflow, or Weights & Biases.
• Excellent ability to communicate across disciplines and work collaboratively.

Nice to Have:

• Deep domain-specific experience in computational biology, genomics, proteomics, or a related field.
• Experience in building DL models for genomic data.
• Experience in NGS data analysis and bioinformatic pipelines.
• Experience with containerised cloud computing environments.

Benefits:

• The US target range of our base salary for new hires is $199,675 - $283,500.
• You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits.