Scientist, Laboratory of AI in Genomics (GIS)

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

An advanced research entity is seeking highly skilled individuals in computer science to contribute to groundbreaking cancer genomics research. The successful candidate will develop algorithms or deep learning models, focusing on de novo genome assembly or generative models. A PhD in a relevant field and experience with deep learning frameworks like Pytorch are essential, along with a strong publication record and proficiency in programming languages such as Python.

Qualifications

• PhD in computer science, math, or physics.
• Experience in deep learning, classical algorithms, or bioinformatics methods.
• Proficient in Python and related libraries.

Responsibilities

• Develop new algorithms or deep learning models focused on cancer genomics.
• Assist in writing grant proposals and managing projects.
• Focus on de novo genome assembly methods.

Skills

Deep learning

Classical algorithms

Pytorch

Python

Education

PhD in computer science, math or physics

Tools

C/C++

Rust

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 of 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 publication or preprint 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.