Overview

EDDC is Singapore's national platform for drug discovery and development, working collaboratively with public sector and industry partners to translate innovations from bench to clinic, tackling complex and unmet medical challenges in oncology, inflammatory and autoimmune diseases. We are looking for a driven Bioinformatics/Data Scientist who combines deep technical expertise with the ability to lead projects end-to-end and shape scientific strategy. You will drive data-driven discovery of therapeutic targets and clinically relevant biomarkers, working at the intersection of multi-omics, machine learning, and translational biology. As part of a dynamic, interdisciplinary team, you will also leverage strategic partnerships locally and globally to advance EDDC's drug discovery mission with agility and impact.

Responsibilities

• Develop and apply computational methods to analyse diverse biological datasets, including genomics, transcriptomics (bulk, single-cell, and spatial RNA-seq), and proteomics, connecting findings directly to target identification and mechanism-of-action studies.
• Build and deploy machine learning and AI models to uncover biological patterns, prioritise therapeutic targets, and generate biomarker hypotheses that advance the drug discovery pipeline.
• Proactively adopt and integrate agentic AI tools — including LLM-assisted coding, automated analysis pipelines, and AI-driven literature synthesis — to accelerate your own and the team's throughput, championing AI-augmented working and continuously improving in-house workflows and platforms.
• Own computational and data projects end-to-end — from problem scoping and experimental design through to delivery, bringing product thinking to prioritise work by impact, and communicating results clearly to senior leadership and cross-functional stakeholders.
• Collaborate closely with biologists, chemists, project leads, and cross-functional teams to integrate scientific, clinical, and commercial data, developing de-risking frameworks that support project prioritisation, elevation, and pipeline decisions.
• Build and manage relationships with external partners in computational biology and AI, ensuring alignment with internal priorities, milestone delivery, and translating complex findings into clear narratives that influence strategic decisions.

Requirements

• PhD in Computational Biology, Bioinformatics, Computer Science, or a related field, with a minimum of 2 years of postdoctoral or equivalent industry experience.
• Demonstrated experience in multi-omics data analysis, including genetics/genomics, bulk and single-cell transcriptomics, spatial transcriptomics, and proteomics, with a clear track record of biological discovery.
• Proficiency in Python and R, and familiarity with cloud-based and on-premises infrastructure, APIs, and workflow development frameworks.
• Demonstrated ability to lead projects end-to-end, manage competing priorities, and deliver results independently in a fast-moving, cross-functional environment.
• Strong communication and stakeholder management skills, with the ability to translate complex analyses into narratives that influence decisions across technical and non-technical audiences.
• Proficiency in machine learning and AI methodologies for large-scale biological data, with experience developing predictive models to guide therapeutic development, is an advantage.
• Hands-on experience with agentic AI tools, LLM-assisted workflows, including biological foundation models such as nucleotide, protein, or single-cell models, in a research or industry context is an advantage.
• Experience in pharmaceutical or biotech companies is an advantage.