IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, discovering how blockchain will reshape the enterprise, and much more. Join a team that is dedicated to applying science to some of today's most complex challenges, whether it’s discovering a new way for doctors to help patients, teaming with environmentalists to clean up our waterways or enabling retailers to personalize customer service.
Your Role and Responsibilities
The work location for this role is either Daresbury Labs or Hursley Labs for a minimum of 2 days a week.
Your role and responsibilities as a member of our global Research Labs will be to:
Create innovative solutions and evaluate them through the design and creation of initial prototypes/tools/pipelines.
Develop toolkits at scale and modelling ecosystems
Evaluate innovative solutions through the design and creation of initial prototypes/tools/pipelines and make them consumable in science and business.
Work with complex and large omics datasets (e.g., microbiome, genomics, transcriptomics, etc.), clinical data and medical images.
Collaborate effectively with our industrial, academic, and internal partners advancing our research and receiving feedback on initial prototypes/tools/pipelines.
Required Technical and Professional Expertise
Undergraduate degree in Computer Science, Software Engineering/Development, Artificial Intelligence/Machine Learning, Engineering, Maths, Physics with experience in bioinformatics research, computational biology or related subjects. Or Undergraduate degree in Bioinformatics, Computational Genomics/Biology with strong experience and skills in computer science, software engineering/development, machine learning.
Strong programming skills, ideally including at least one common AI/ Machine Learning framework.
Experience in collaborative software development projects, e.g., open-source projects or software development projects for research.
Experience with DevOps tools for collaborative software development.
Familiarity with building application frameworks and understanding of API design patterns.
Ability to work at the interface between Healthcare, Life Sciences and Informatics.
Familiarity with omics data processing and development and/or maintenance of bioinformatic pipelines.
Experience with large-scale data management and analysis, especially omics data.
Demonstrated ability to organize, prioritize, and multi-task in a fast paced, changing, and agile development environment to meet deadlines.
Effective written and verbal communication and interpersonal skills.
Preferred Technical and Professional Expertise
Postgraduate degree in Computer Science, Software Engineering/Development, Artificial Intelligence/Machine Learning, Engineering, Maths, Physics with experience in bioinformatics research, computational biology or related subjects. Or Postgraduate degree in Bioinformatics, Computational Genomics/Biology with strong experience and skills in computer science, software engineering/development, machine learning.
Strong experience and skills in Data Science, Machine Learning and Deep Learning.
Experience in scientific research or software engineering for research.
Experience in cloud native application design and development leveraging microservices and cloud native patterns, workflow, event-driven architecture.
Experience with cloud-native environments, such as AWS (S3, lambda, CloudTrails, etc) or other cloud vendors.
Experience building and deploying across multiple cloud environments.
Experience using containerised cloud platforms such as Kubernetes or OpenShift.
Working experience building workflows and AI models in platforms such as Ray, Pytorch, MLFlow, etc.
Experience creating (or at least using) APIs and SDKs.
Experience in the use of Jupyter notebooks and Python libraries such as pandas, numpy, scikit-learn, matplotib for prototyping and application development.
Experience working data and models for life science and healthcare (e.g., omics data, clinical data and medical imagery).
Familiarity with bioinformatics programming environments such as BioPython/BioPerl.