Astex Pharmaceuticals is a world leader in innovative drug discovery and development. The company has successfully applied its proprietary Fragment-Based Drug Discovery platform to generate multiple new drug candidates that are progressing in clinical development. Successful collaborations have led to two launched oncology drugs (Kisqali® partnered with Novartis and Balversa® partnered with Janssen). Astex continues to grow and focuses on Oncology and Neurological Disorders.

The Opportunity

The bioinformatics team at Astex works with multi-disciplinary project teams driving new targets, preclinical and clinical research, with a focus on NGS technologies, multi-omics and functional genomics. We are looking for a candidate with a strong background in developing AI and machine-learning methods and algorithms to identify new targets and gene-disease associations and derive disease insights from multi-modal data.

Principal Responsibilities

• Developing and implementing deep-learning approaches to analyse diverse multi-modal data (e.g. genomics, transcriptomics, imaging) to identify novel drug targets, biomarkers and drug mechanisms
• Developing predictive models using statistical, mathematical and machine-learning methods for biomarker identification and patient stratification strategies
• Working with bioinformaticians, statisticians and biologists to support experimental design and build data processing and analysis pipelines
• Evaluating and assessing new machine-learning approaches developed by the research community for adoption and implementation in-house

Candidate Profile

• PhD in mathematics, computer science, engineering, or another relevant numerical/computational discipline; alternatively, equivalent experience in relevant research (5-10 years)
• Experience with exploration of complex data to identify key opportunities and demonstrable ability to create actionable outputs
• Experience with advanced statistical and machine learning concepts such as Bayesian optimisation, probabilistic modelling, and neural-network design (Tensorflow/PyTorch/Keras)
• Excellent coding skills (e.g., Python, R), experience with general numerical programming (SciPy/NumPy) and software engineering.
• Experience in applying machine learning approaches to multi-omics data would be highly desirable
• Experience with graph databases and formats (e.g., Neo4j) and software/ML libraries relevant to network analysis would be desirable
• Ability to work independently and experience with line management

Why Astex

We offer excellent training and development opportunities as well as highly competitive salary and benefits package including hybrid and remote working options to promote a flexible and inclusive work environment.

At Astex we embrace diversity and equality of opportunity. We are committed to building an inclusive and diverse Company representing all backgrounds, harnessing industry-leading scientific innovation and behaviours.