Overview: EDDC is the national platform for drug discovery, committed to work with the Singapore ecosystem to translate scientific discoveries into life-changing therapeutics for patients. We leverage state-of-the-art computational and machine learning approaches to uncover insights from large-scale and multidimensional data sources, and to tackle complex and unmet medical challenges in disease areas such as oncology, inflammatory and autoimmune diseases

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We are seeking a skilled Software Developer to join the computational sciences team to contribute significantly to building an organizational-wide ML/AI-ready data foundation, focusing on laboratory automation, integration solutions, and software development. The role involves close collaboration with wet-lab scientists, computational scientists/engineers, and IT teams to design, develop, and implement cost-effective, robust solutions utilizing a combination of commercial software and in-house development. Leveraging modern tech stacks and APIs, this position will facilitate seamless laboratory operations and data management in a multi-disciplinary environment with both biological and chemical data.

Key Responsibilities:

1. Application Development and Integration:

• Develop and maintain software solutions to integrate laboratory informatics systems with automated hardware systems and robotic laboratory equipment.
• Automate workflows related to sample management, inventory tracking, assay preparation, and data analytics.
• Collaborate with scientists and engineers to understand requirements and translate them into efficient software solutions.

2. Legacy System Modernization

• Assess existing systems, recommending and implementing modernization strategies that improve functionality, scalability, and ease of maintenance.
• Utilize modern software frameworks, cloud-based technologies, and AI-driven coding tools, if relevant, to streamline system modernization.

3. Data Integration and Automation

• Develop API-driven integrations and automated workflows connecting laboratory software, hardware, and internal/external databases.
• Ensure robust, real-time synchronization of data across various laboratory systems.
• Develop APIs and integration layers to connect applications cross different systems (e.g., chemical structure databases, property databases, and regulatory systems).

4. ML/AI-Ready Data Foundation Development:

• Collaborate with computational scientists and data engineers to design and implement an organizational-wide ML-ready data foundation.
• Develop tools and pipelines to ensure data is clean, well-structured, and accessible for machine learning and analytics.
• Integrate data from diverse sources (e.g., compound registration, inventory tracking, laboratory systems, and external databases) into a unified data infrastructure.

5. Communication and Collaboration

• Work closely with wet-lab scientists, computational scientists, data engineers, and IT team to clearly identify requirements and collaboratively develop solutions.
• Provide technical documentation, training, and support to users and stakeholders.
• Work closely with the cross-functional colleagues and data engineer to ensure applications are compatible with the organization's data infrastructure and Single Source of Truth (SSOT) initiatives.

Required Skills/Qualifications:

• Bachelor's or Master's degree in Computer Science, Software Engineering, Automation Engineering, Bioinformatics or a related field.
• 2-3 years of experience in software development, scripting, or automation-focused roles.
• Strong proficiency in programming/scripting languages (eg. Python, Java, SQL, etc.) and experience with RESTful API integration.
• Experience in laboratory automation systems and developing integrations involving biological or chemical informatics.
• Experience with legacy system modernization and cloud-based solutions.
• Strong problem-solving skills and ability to work in a multidisciplinary environment.
• Excellent communication and teamwork skills, capable of bridging computational and laboratory teams.

Preferred Skills/Qualifications:

• Familiarity with open-source integration platforms and workflow management tools (e.g., KNIME, Apache Airflow, SiLA2).
• Experience using AI-assisted coding tools (e.g., GitHub Copilot, Cursor) to enhance productivity and streamline development workflows.