Scientist, Laboratory of AI in Genomics (GIS)

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading research organization in Singapore is seeking talented individuals in computer science to join their cancer genomics research team. The role involves developing algorithms and deep learning models focusing on cancer genomes, including de novo genome assembly methods. Candidates should have a PhD in computer science, math, or physics, with experience in deep learning and bioinformatics tools. This position offers the chance to contribute significantly to cancer research and therapeutics development.

Qualifications

• Experienced in deep learning or classical algorithms.
• At least one or two first-author publications or preprints.
• Keen interest in programming, algorithm development, mathematics.

Responsibilities

• Develop new algorithms or deep learning models.
• Assist in writing grant proposals.
• Manage projects.

Skills

Deep learning

Classical algorithms

Pytorch

C/C++

Rust

Python

Education

PhD in computer science, math or physics

Tools

Bioinformatics tools for variant calling

Bioinformatics tools for de novo assembly

Bioinformatics tools for long read sequencing analysis

Job description

Job duties and responsibilities:

We invite brilliant minds in computer science to join us at the cutting-edge of cancer genomics research, harnessing the power of artificial intelligence or classical algorithms. Your job will involve either the development of new algorithms or deep learning models focusing on understanding cancer genomes. The focus will be on de novo genome assembly methods for reconstructing cancer genomes or developing new generative RNA/DNA/epigenome/epitranscriptome foundation models and agents aiming to speed up therapeutics development.

The duties include assisting in writing grant proposals and managing projects.

Job Requirements:

• PhD in computer science, math or physics
• Experienced in deep learning or classical algorithms
• Experienced in Pytorch for deep learning or C/C++ or Rust for classical algorithms
• At least one or two first-author publications or preprints from your PhD and/or MSc work.
• Experience with bioinformatics methods and tools for (a) variant calling, and/or (b) de novo assembly and/or (c) long read sequencing analysis;
• Proficiency in Python, and genomics and machine learning libraries therein.
• Keen interest in programming, algorithm development, mathematics, complexity, and puzzles.

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.