Senior Bioinformatics Scientist - RNA & ML for Genomics

BERKELEY EDUCATION ALLIANCE FOR RESEARCH IN SINGAPORE LIMITED; Singapore; On-site; SGD 110,000 - 180,000; Full time

Job summary

The Berkeley Education Alliance for Research in Singapore Limited seeks a bioinformatician to lead computational analysis of SURF project data and to develop advanced machine-learning models on internal and external data. The role spans data lifecycle, from design to publication, with emphasis on reproducibility and scalability within the SURF program.

Candidates should have a PhD in a quantitative field and 5–10 years in research settings, with expertise in ML, RNA biology data analysis, and

Qualifications

• PhD in bioinformatics, computational biology, data science, ML or related field with 5–10 years experience.
• Experience with CNNs, RNNs, GANs, GNNs, RAGs and transformers on biological data.
• Proficiency in R and Python; containerization with Docker/Singularity; HPC or cloud computing.
• RNA biology data analysis, including RNA-seq like scRNA-seq or scATAC-seq.
• Experience collaborating with wet-lab researchers and co-authorship of publications.

Responsibilities

• Data Analysis and Computational Modeling of large-scale -omics datasets.
• Develop ML models for classification, inference, or prediction of biological data.
• Design and maintain reproducible bioinformatics pipelines.
• Collaborate with wet-lab scientists on experimental design and interpretation.
• Ensure data governance, reproducibility, and documentation.

Skills

Machine-learning models

CNNs

RNNs

GANs

GNNs

Transformers

R

Python

Docker

Singularity

HPC

Cloud computing

RNA biology data analysis

Education

PhD in bioinformatics, computational biology, data science, machine learning, or a related quantitative discipline

Tools

Docker

Singularity

HPC

Cloud platforms

Job description

The Berkeley Education Alliance for Research in Singapore Limited seeks a bioinformatician to lead computational analysis of SURF project data and to develop advanced machine-learning models on internal and external data. The role spans data lifecycle, from design to publication, with emphasis on reproducibility and scalability within the SURF program.

Candidates should have a PhD in a quantitative field and 5–10 years in research settings, with expertise in ML, RNA biology data analysis, and