Overview Of Role
Are you a talented Machine Learning Engineer with a passion for advancing the field of bioinformatics? We are seeking a skilled individual to join our team working on an innovative discovery platform, known as KnetMiner. KnetMiner transforms the integration of genomics, genetics, and literature information into comprehensive knowledge graphs, empowering researchers with powerful tools to explore, analyze, and interpret biological data in innovative ways.
As a Machine Learning Engineer within the KnetMiner team, you will play a pivotal role in developing cutting-edge AI functionality to enhance the capabilities of our platform. Your work will directly impact the ability of researchers worldwide to make discoveries in genomics and genetics. You will collaborate closely with a multidisciplinary team of bioinformaticians, data engineers and software engineers to drive innovation in bioinformatics.
This role will provide opportunities to:
- Create and implement machine learning algorithms and models to enhance data analysis, knowledge extraction, and predictive capabilities from graph and literature data.
- Collaborate closely with data engineers and domain experts to seamlessly integrate various data types (genomics, genetics, literature) into comprehensive and intuitive knowledge graphs.
- Utilise machine learning approaches, including deep learning, reinforcement learning, to extract valuable insights from high-dimensional biological data such as DNA sequencing, gene expression, and proteomics data.
- Develop retrieval augmented generation approaches that combine knowledge graphs and large language models to tell the plotlines of complex traits.
- Work on user interface development and other software components related to machine learning features in KnetMiner.
Essential Skills & Knowledge:
- Strong programming skills in languages such as Python and proficiency in relevant libraries (e.g. PyTorch, scikit-learn).
- Solid understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning.
- Experience with data manipulation, feature and prompt engineering techniques.
- Experience with version control systems (e.g., Git) for code management.
- Strong problem-solving abilities and adaptability to new challenges.
- Effective communication skills to collaborate with interdisciplinary teams.
Desired Skills & Knowledge:
- Interest in developing machine learning solutions for bioinformatics or genomics applications.
- Knowledge of graph databases, specifically Neo4j and Cypher.
- Experience with cloud computing platforms and machine learning APIs.
- Knowledge of large language models and natural language processing.
- Familiarity with big data technologies and distributed computing (e.g. Hadoop, Spark).
- Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes).
If you are a talented Machine Learning Engineer who is eager to harness the power of AI and knowledge graphs to drive innovation in genomics and genetics research, we invite you to join us. Be a vital part of our transformative project that is shaping the future of biological discovery.
Interested but not sure you tick every box? Research shows that some people are less likely to apply for jobs unless they meet every single criteria. At Rothamsted we are committed to building diverse teams so please apply even if your past experience doesn’t align perfectly with the requirements – you might just be the perfect fit!
This is a fixed-term 2-year appointment in the first instance with a salary based on experience. As part of our flexibility to working arrangements, the institute operates a policy whereby regular homeworking arrangements can be considered. For any enquiries, please contact keywan.hassani-pak@rothamsted.ac.uk.
Closing Date: 27 October 2023
Interviews: 7 November 2023
About The Company
Established in 1843, Rothamsted Research is one of the UK’s leading Research Institutes delivering world class agricultural science. Our commitment to learning and development, equality and diversity as well as creating a positive work life balance, enable a welcoming environment for all prospective employees. As part of our flexibility to working arrangements for our staff, the institute operates a policy whereby regular homeworking arrangements can be considered.
We have an attractive benefits package including 25 days annual leave, a generous pension scheme and an attractive campus offering cultural and recreational activities. Rothamsted Research values its commitment to equality and diversity in its workforce and we particularly encourage applications from women, disabled and Black, Asian and Minority Ethnic (BAME) candidates, as these groups are currently under-represented within the organisation.
