Project Overview

Deep learning and AI are revolutionizing drug discovery, yet current models fall short of harnessing the vast diversity of biological data being generated. This project offers an opportunity to develop groundbreaking multimodal models for drug discovery and healthcare. By combining cutting-edge machine learning and generative AI approaches—spanning small molecule drug discovery, protein design, DNA and protein language models, genomic datasets, and electronic health records—we aim to create entirely new classes of AI foundation models that will revolutionize healthcare.

Job Description

We are seeking a passionate and innovative Deep Learning Research Engineer to join our interdisciplinary team of biologists and computer scientists from MIT, NUS, and NTU. You will pioneer AI-driven approaches to accelerate the discovery of new drugs and diagnostics, leveraging unique datasets and state-of-the-art technologies.

• Train advanced deep learning models to transform drug discovery.
• Work with multimodal datasets, including drug screening results, genomic data, and electronic health records.
• Contribute to the discovery of new antibiotics and the design of novel diagnostic tests.
• Learn from and collaborate with experts in biology and computer science.
• Present research findings and publish in leading journals.

Requirements

• Bsc or MSc in Computer Science, Bioinformatics, or a related field.
• Proven experience in training large deep learning models.
• Familiarity with reinforcement learning, generative AI, or statistical modeling is a plus.
• Experience with large biological datasets or healthcare records is desirable, but a strong willingness to learn is equally valued.

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.