Job Opportunities

We are looking for a Research Fellow position in: 

A hybrid mechanistic modelling and AI approach for efficacious prediction of optimal cell-free chemical biosynthesis 

Background:

The sustainability of chemical supplies is critical to our country’s competitiveness. On this, cell-free production offers a promising solution. Among the potential computational methods for optimizing its yield, black-box AI or machine learning techniques alone cannot make reliable prediction based on molecular inputs, whereas pathway modelling requires mechanistic details that are mostly unavailable.  

Objective/Outcome:  

To address both limitations, this project aims to develop a standardized approach for modelling and optimizing pathway production, with both the applicable rate laws and their parameter values learnt using AI.  

The Research Fellow will also demonstrate his/her effectiveness via an in-silico proof-of-concept study as the first step towards enhancing the efficiency and yield of biomanufacturing. He/She will also contribute to manuscript writing, the dissemination of findings and intellectual property development. 

Requirements: 

• PhD or equivalent in computer science, computer engineering, data science, computational biology, or bioinformatics. 

• Good track record in research efforts/IP development 

• Knowledge of Linux and Python language necessary; basic knowledge on R. 

• Comfortable working with linux-based software and pipeline 

• Molecular biology knowledge a plus

• Willingness to learn and explore unknown research territory

Interested candidate pls contact Dr Yeo Hock Chuan for details: yeohc@bii.a-star.edu.sg 

We have a 6-month internship project for an undergraduate student.

Project: Functional annotation of Skin Fungus, Malassezia’s genome.

Malassezia is the dominant fungal species on all human skin, healthy and diseased. They are associated with skin diseases ranging from dandruff, eczema, atopic dermatitis to adenocarcinoma. However, the actual biology is unclear as this organism is poorly studied. But association is clear as the application of antifungal on 50% of the dandruff sufferers show improvement. 

Objective/Outcome: The aim of this project is to functionally annotate Malassezia genomes using bioinformatics and data analytic tools.  The student will first be expected to manually curate annotations and perform literature review, and second, use various software and databases to extract valuable information. As there are currently no official protocols for fungal genome annotation, the student is intended to explore innovative bioinformatics methods and pipeline guided by the project supervisor. The intern will successfully learn the skillset of genome annotation and better perspective of fungal biology.

Requirements:

• Undergrad in computer science, computer engineering, data science or bioinformatics, and currently residing in Singapore.

• Knowledge of linux, python necessary. Basic knowledge on R.

• Comfortable working in bioinformatics, its related software and pipeline.

• Interest in genome biology is a plus.

Stipend: A stipend will be paid in accordance with ASTAR rules.

Interested candidate please contact Lee Shi Mun for details: lee_shi_mun@asrl.a-star.edu.sg