Research software Engineer - Large Language Model focus

at  European Molecular Biology Laboratory EMBL

RESEARCH SOFTWARE ENGINEER - LARGE LANGUAGE MODEL FOCUS

Employer
European Molecular Biology Laboratory (EMBL)
Location
Hinxton
Salary
Competitive
Closing date
20 May 2024
Discipline
Life Science
Job Type
Engineer
Employment - Hours
Full time
Duration
Fixed term
Qualification
Masters
Sector
Academia
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WHAT ELSE YOU NEED TO KNOW

• Contract duration: This position is a 3 year fixed-term project-limited contract.
• International applicants: We recruit internationally and successful candidates are offered visa exemptions. Read more on our page for international applicants.
• Diversity and inclusion: At EMBL-EBI, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought. We encourage applications from women, LGBTQ+ and individuals from all nationalities.
• EMBL is a signatory of DORA. Find out how we implement best practices in research assessment in our recruitment processes here.
• Job location: This role is based in Hinxton, near Cambridge, UK. You will be required to relocate if you are based overseas and you will receive a generous relocation package to support you.

We are seeking a highly skilled and motivated Research Software Engineer with expertise in Python and Large Language Model (LLM) integration to join the AI knowledge management project for a period of 3 years. This role is central to our mission of advancing open science and robust drug development. You will be a key player in designing and operating software that integrates cutting-edge knowledge graphs, LLMs and ML techniques into our biomedical data processing and drug discovery platforms.
We are open to applicants at various career stages, but we are particularly interested in individuals who are eager to utilise cutting-edge technologies to address complex challenges in biological knowledge extraction. This position would be embedded within the Open Targets project team in the Saez-Rodriguez Group at the European Bioinformatics Institute and benefit from joint supervision with Sebastian Lobentanzer in the Saez-Rodriguez Group at Heidelberg University Hospital (UKHD).
You will work collaboratively across the project group with other experts in ML/AI, NLP, data integration and product delivery across ChEMBL, ePMC, Open Targets and Heidelberg University Hospital on a common goal to integrate cutting-edge technology for knowledge extraction, representation and integration to help drug discovery scientists to generate therapeutic hypotheses.
As a crucial member of the project team, you will design, build, and operate cloud-first open-source software that interfaces with large-scale biomedical data and drug discovery. You will contribute to the development of current and future informatics tools designed to support the identification and prioritisation of drug targets. Leveraging cutting-edge technologies and the expertise of our product owners and industry stakeholders, you will work in a dynamic, multidisciplinary, international environment to tackle a wide range of algorithmic and technical challenges.

As part of a dynamic, collaborative, and international team, you will be responsible for:

• Developing and maintaining backend (Python) software, integrating databases and LLMs (https://biocypher.github.io/biochatter).
• Investigating and implementing open source LLMs/conversational AI agents for use in web applications (chatbot) and therapeutic hypothesis generation.
• Accessing bespoke knowledge graphs across OT data for specific use cases and assisting in the integration into the Open Targets Platform ecosystem.
• Collaborating with the OT industry and academic partners to collect requirements and assess, prioritise, validate and refine the developed methods.
• Taking ownership of the design and development of new features and pipelines, and independent problem-solving to resolve complex issues.
• Actively disseminating the outcomes of the project to the scientific community and stakeholders through well-crafted presentations and publications.