Bioinformatics/Data Scientist (Computational Biology, EDDC)

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 80,000 - 100,000; Full time

Job summary

A leading research organization in Singapore seeks a skilled Bioinformatics/Data Scientist to develop analytical methods for diverse biological datasets. You will work in a collaborative team, leveraging multi-omics and machine learning to drive drug discovery. Ideal candidates hold a PhD and have experience with machine learning and data analytics in biological contexts. A strong track record in multi-omics and collaboration is essential. This role offers a dynamic environment at the forefront of computational biology.

Qualifications

• PhD with strong emphasis on data analytics and machine learning.
• 2 years of postdoc experience or equivalent in industry.
• Experience in multi-omics data analysis and machine learning application.

Responsibilities

• Develop computational methods to analyse biological datasets.
• Leverage machine learning to uncover biological patterns.
• Collaborate with scientists and communicate findings through reports.

Skills

Multi-omics data analysis

Machine learning

Python

R

Collaboration

Education

PhD in Computational Biology or related field

Tools

Cloud-based database services

APIs

Job description

Overview

At EDDC, Singapore’s national platform for drug discovery and development, we are committed to discovering and developing novel therapeutics by working collaboratively with both public sector and industry partners, translating innovations from bench to clinic. This includes tackling complex and unmet medical challenges in disease areas such as oncology, inflammatory and autoimmune diseases. EDDC is now seeking a highly skilled and motivated Bioinformatics/Data Scientist to join the Computational Biology group to drive data‑driven discovery of therapeutic targets and clinically relevant biomarkers, enabling a wholistic understanding of human disease biology. As part of a dynamic, interdisciplinary team, you will apply multimodal data analytics and machine learning to accelerate and enhance the drug discovery process. The role will also leverage strategic partnerships—both locally and globally—to refine and advance EDDC’s solutions with agility and impact.

Responsibilities

• Develop and apply computational methods to analyse diverse biological datasets, including genomics, transcriptomics (bulk, single‑cell, and spatial RNAseq) and proteomics data.
• Leverage machine learning and AI to uncover meaningful biological patterns and build predictive models to support target identification and mechanism‑of‑action studies.
• Collaborate closely with biologists, chemists, and cross‑functional scientists to prioritize novel therapeutic targets and biomarkers, design and analyse experiments, and effectively communicate findings through scientific reports and presentations.
• Drive and support collaborations with external partners in computational biology and AI, ensuring alignment with internal priorities and project milestones.
• Stay at the forefront of computational biology and AI developments, proactively implementing new methodologies to improve in‑house workflows and enhance EDDC’s computational platforms.

Requirements

• PhD in Computational Biology, Bioinformatics, Computer Science, or a related field, with a strong emphasis on data analytics and machine learning in biological contexts. Minimally 2 years of postdoc experience or equivalent in industry settings.
• Demonstrated experience in multi‑omics data analysis (eg. genetics/genomics, bulk, single‑cell, and spatial transcriptomics, proteomics, etc.) and the application of machine learning in biological research.
• Proficiency in Python and R, and familiarity with cloud‑based and on‑premises database services, APIs and workflow development frameworks.
• Excellent communication and collaboration skills, with experience working independently and in multi‑disciplinary teams.
• Keen to learn new techniques and adaptable to changing priorities.
• Proficiency in machine learning and AI methodologies for analysing large‑scale biological data, with a proven track record of developing predictive models to guide therapeutic development and strategy is an advantage.
• Industry experience in pharmaceutical or biotech companies is an advantage.