Description

The Genome Institute of Singapore (GIS) is the national flagship for genomic sciences, driving cutting-edge research at the intersection of biology, engineering, and medicine. This position is offered in the Laboratory of AI in Genomics, led by Prof. Mile Šikić, which uses advanced bioinformatics and deep learning approaches to develop next-generation models for genomic data analysis. We are group a of computer scientist with a mission to improve healthcare using advance deep learning models. Located in the heart of Singapore’s thriving biomedical hub, GIS offers a dynamic and collaborative environment, with close ties to world-class universities (NUS and NTU), pharmaceutical companies, and biotech start-ups. Joining our team means working on transformative projects with real-world impact, while benefiting from Singapore’s vibrant research ecosystem and strong support for innovation.

Project background

De novo genome assembly has been one of the most challenging problems in genomics. However, with the development of new long-read sequencing technologies, new assemblers, and manually curated high-quality benchmarks, including CHM13, HG002 and I002C, assembling most human chromosomes T2T has become a routine task.

This project will focus on a more challenging task: assembling human cancer genomes, which are especially difficult due to cancer genome heterogeneity. Using the fact that we can reconstruct normal tissue genomes routinely, we aim to reconstruct cancer genomes using a combination of traditional algorithms and AI.

Job description

We are looking for a highly motivated researcher to:

- Adapt the HERRO error correction model to cancer genomes

- Develop an agent for normal and cancer genome assembly

Profile

We welcome applications from candidates with:

- A bachelor’s or master’s in computer science, applied mathematics, or a related field

- Proven experience in AI with focus on building agents

- Experience in C/C++/Rust and Python programming and solid software engineering skills are preferable

- A structured, independent, proactive and collaborative working style

We offer

• A fully funded position
• Professional development opportunities, including support for grant applications and participation in conferences and workshops
• Access to state-of-the-art research infrastructure, including NSCC’s high-performance computing clusters
• A dynamic, interdisciplinary, and collaborative research environment
• The position is initially offered for two years, with the possibility of renewal

How to apply

We look forward to receiving your application with the following documents:

• Letter of Motivation
• CV
• Diplomas & Transcripts

We accept applications submitted via email directed to Prof. Šikić at mile_sikic@a-star.edu.sg.