Job Description

We are seeking a talented and motivated Software Engineer to join our innovative drug discovery team. As a Software Engineer, you will play a pivotal role in developing and optimizing the computational tools and infrastructure that power our research, with a strong focus on leveraging and developing the capabilities of the AIDD LeadFactory.



Key responsibilities



Design, develop, and maintain robust, scalable, and efficient software solutions for various stages of the drug discovery pipeline (e.g., cheminformatics, bioinformatics, molecular modeling, data analysis).

Collaborate closely with computational chemists, biologists, data scientists, and other engineers to translate scientific requirements into technical specifications and deliver impactful software.

Implement and optimize algorithms for large-scale data processing, scientific simulations, and machine learning models.

Contribute to the development and maintenance of our internal computational platforms and infrastructure.

Ensure code quality, test coverage, and documentation for all developed software.

Stay up-to-date with the latest advancements in software engineering, computational chemistry, and drug discovery.



Qualifications



Master's degree in Computer Science, Software Engineering, Computational Chemistry, Bioinformatics, or a related field.

Minimum 5 years of experience in software development, with a strong preference for experience in drug discovery, cheminformatics, bioinformatics, or a related scientific domain.

Proficiency in programming languages commonly used in scientific computing (e.g., Python, C++, Java, R).

Experience with scientific libraries and frameworks (e.g., RDKit, OpenEye, NumPy, SciPy, Pandas, scikit-learn, TensorFlow/PyTorch), and web-based software platforms.

Familiarity with relational and/or NoSQL databases.

Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes) is a plus.

Strong problem-solving skills and a passion for tackling complex scientific challenges.

Excellent communication and teamwork skills.



Bonus points for experience with



Machine learning applications in drug discovery.

High-performance computing (HPC) environments.

Developing user interfaces and web-based platforms for scientific applications.

Contributing to open-source scientific software

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

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