Junior Scientist, EDDC

Agency for Science, Technology and Research (A*STAR); Singapore; On-site; USD 50,000 - 80,000; Full time

Job summary

Join a pioneering organization in Singapore focused on drug discovery! As a junior scientist in the Computational Chemistry team, you will leverage cutting-edge artificial intelligence techniques to enhance small molecule drug discovery efforts. This role offers a unique opportunity to collaborate with experts across various fields, including biology and chemistry, to drive innovative solutions in drug design. If you're passionate about applying your knowledge in machine learning and computational methods to real-world challenges in healthcare, this is the perfect opportunity to make a significant impact in the industry.

Qualifications

• Bachelor degree in chemistry, biology, or computer science with drug discovery knowledge.
• Experience with machine learning algorithms and programming languages, preferably Python.

Responsibilities

• Develop and apply computational methods for small molecule drug discovery.
• Collaborate with biologists and chemists for hit identification and lead optimization.

Skills

Drug Discovery Knowledge

Machine Learning

Deep Learning

Python Programming

Problem Solving

Communication Skills

Education

Bachelor in Chemistry

Bachelor in Biology

Bachelor in Computer Science

Tools

Sci-kit Learn

Keras

TensorFlow

PyTorch

Job description

Experimental Drug Development Centre (EDDC) is a drug discovery national platform in Singapore focused on translating upstream research into therapeutic assets to generate value for Singapore. EDDC is looking for a junior scientist to join the Computational Chemistry team to strengthen our efforts by leveraging Artificial Intelligence for small molecule drug discovery.

As part of the team, the candidate will be developing and applying cutting-edge computational methods such as generative AI for de novo molecular design toward different classes of protein targets. The staff will also have the opportunity to collaborate closely across functions, with biologists and chemists to support hit identification, hit-to-lead design, and lead optimization, with CADD scientists to develop machine learning models for in-house discovery programs.

Key Requirements

• Bachelor degree in the field of chemistry/biology/computer science with good knowledge in drug discovery and design
• Ideal candidates should have expertise in at least one of the following: structure-based drug design, machine/deep learning model building and training
• Experience with machine learning algorithms (e.g., Random Forest, Support Vector Machine, Deep Neural Networks) and packages (e.g., Sci-kit Learn, Keras, TensorFlow, PyTorch) is a plus.
• Experience with one scripting or programming language (Python preferred) is preferred.
• Track record of applying machine learning, in particular modern deep learning approaches, to solve relevant biological or chemical problems is required.
• Personal attributes of independence, integrity, creativity, problem solving, and strong work ethic.
• Excellent communication skills.