Bio-ML Scientist (Metabolic Modelling) - Generative Biology Insititute

Key Responsibilities

• Research, design and build AI and machine learning systems to address GBI’s research challenges in synthetic biology, genome design, and molecular evolution.
• Lead and contribute to collaborative projects with other MLEng team members, GBI researchers and staff, relevant colleagues across EIT, and external collaborators.
• Work closely with GBI scientists in co-creation of research projects and development of fit-for-purpose computational solutions.
• Provide expert computational biology knowhow to GBI researchers and scope novel avenues of research.
• Interact with the Bioinformatics and Scientific Compute platform teams to support the development of GBI data flows and MLOps.
• Ensure compliance with best practices in ML engineering , including robust and reproducible training pipelines, as well as versioning and documentation of data, models, and code.
• Keep abreast of progress in AIxBio and make use of strategic learning opportunities.
• Lead and contribute to research publications in prestigious venues.
• Organise and prioritise work , operating at the highest standard in the face of multiple competing deadlines.

Essential Knowledge, Skills and Experience

• PhD degree in a suitable field including, but not limited to, molecular biology, biochemistry, mathematics, computer science, computational biology, engineering, or related discipline.
• Experience in building machine learning models for biological design or discovery tasks , involving processing, visualizing, and analysing various data modalities.
• Ability to abstract high-level biological questions and translate them into actionable computational tasks, evidenced by previous achievements in a comparable industry role, or a promising publication record in scientific journals and technical conferences.
• Ability to learn quickly and dive into a range of problem spaces and computational methods.
• Ability to work and communicate with and within diverse and multidisciplinary teams.
• Fluency in one or more scientific programming languages (Python, R, Julia, etc.) with experience in best practices in machine learning, including documentation.
• Excellent written and oral communication skills for diverse audiences, including colleagues without a computational background.
• Excellent time management skills across competing tasks requiring rapid context switching.

Desirable Knowledge, Skills and Experience

• Two years of industry or postdoctoral experience in similar roles.
• Proven experience with integration of machine learning methods with genome-scale metabolic models.
• Proven experience with best practices and established software pipelines for genome-scale metabolic modelling, including automated model construction from ‘omics data, flux balance analysis, flux sampling, sensitivity analysis, and related methods in constraint-based modelling.

Our Benefits

• Travel Allowance
• Bonus
• Pension - Employer contribution 7.5%, minimum employee contribution 5%
• Life Assurance.
• Income Protection
• Private Medical Insurance as standard for you, your partner and any dependents. Including hospital Cash Plan
• Employee discounts
• Electric car scheme
• Nursery Salary Sacrifice scheme
• Cycle to Work Scheme
• Family Planning
• Neurodiversity support including advise and assessments
• Coaching & Therapy services

Working Together – What It Involves