Research Engineer, Centre for Frontier AI Research, IAIC

A*STAR - Agency for Science, Technology and Research; Singapore; Presencial; SGD 120.000 - 190.000; Jornada completa

Descripción de la vacante

A Research Engineer at A*STAR - Agency for Science, Technology and Research in Singapore will develop and implement AI methods to support drug discovery for RNA targets. You will build computational tools for RNA structure modelling, molecular interaction prediction, and compound screening, collaborating with an interdisciplinary team.

The role requires strong Python, ML/DL framework experience (PyTorch or TensorFlow), data processing skills, and a passion for applying AI to RNA biology and drug

Formación

• Master’s degree in Computer Science, Bioinformatics, Computational Biology, Computational Chemistry, or a related discipline.
• Strong Python programming skills and familiarity with version control, testing, and documentation.
• Hands-on experience with machine learning or deep learning frameworks such as PyTorch or TensorFlow.
• Experience processing scientific datasets and evaluating predictive models.
• Strong analytical and problem-solving skills, with the ability to work independently and collaboratively.
• Interest in applying AI to RNA biology and drug discovery.

Responsabilidades

• Implement and optimise machine learning models for RNA structure prediction and RNA-small molecule interaction modelling.
• Develop data processing pipelines for RNA sequences, structures, chemical compounds, and experimental measurements.
• Train, fine-tune, and evaluate models using GPU computing resources.
• Support computational screening and prioritisation of compounds for experimental validation.
• Collaborate with researchers to integrate experimental results into computational workflows.
• Maintain reproducible code, technical documentation, and model evaluation pipelines.

Conocimientos

Python

PyTorch

TensorFlow

ML frameworks

Data processing

Analytical skills

Collaboration

Publications

Educación

Master's degree

Herramientas

Git

Testing

Documentation

Descripción del empleo

Job Summary

We are seeking a motivated Research Engineer to develop and implement AI methods that support drug discovery for RNA targets. The successful candidate will work with an interdisciplinary team to build computational tools for RNA structure modelling, molecular interaction prediction, and compound screening.

Key Responsibilties

• Implement and optimise machine learning models for RNA structure prediction and RNA-small molecule interaction modelling.
• Develop data processing pipelines for RNA sequences, structures, chemical compounds, and experimental measurements.
• Train, fine-tune, and evaluate models using GPU computing resources.
• Support computational screening and prioritisation of compounds for experimental validation.
• Collaborate with researchers to integrate experimental results into computational workflows.
• Maintain reproducible code, technical documentation, and model evaluation pipelines.

Job Requirements

• Master's degree in Computer Science, Bioinformatics, Computational Biology, Computational Chemistry, or a related discipline.
• Strong Python programming skills and familiarity with software development practices, including version control, testing, and documentation.
• Hands-on experience with machine learning or deep learning frameworks such as PyTorch or TensorFlow.
• Experience processing scientific datasets and evaluating predictive models.
• Strong analytical and problem-solving skills, with the ability to work independently and collaboratively.
• Interest in applying AI to RNA biology and drug discovery.
• Publications in leading peer-reviewed journals or conferences in AI, computational biology, bioinformatics, or drug discovery, such as Nature Communications, Nature Machine Intelligence, NeurIPS, ICML, and ICLR, would be an advantage. Candidates with strong evidence of practical implementation through research projects, software contributions, or AI model development are also encouraged to apply.

Desirable Experience

• Familiarity with RNA structure, cheminformatics, molecular modelling, or structure-based drug discovery.
• Experience with language models, graph neural networks, or other models for biological sequences and molecular structures.
• Familiarity with chemical probing data, such as SHAPE or DMS measurements.
• Experience with GPU computing, high-performance computing clusters, or distributed model training.