AI Scientist (Protein foundation models)

Openprotein; Singapore; On-site; SGD 80,000 - 120,000; Full time

Benefits offered by this job

Competitive base salary

Health and dental insurance

Equity options

Job summary

OpenProtein in Singapore is looking for a dedicated individual with a PhD focusing on ML/AI for biomolecules. Your role will involve developing deep learning solutions for protein structure prediction and other biomolecular challenges, alongside leading research projects from the ground up.

The ideal candidate will possess a strong background in Python and deep learning frameworks such as Pytorch. A collaborative mindset and ability to manage stakeholder communications are key parts of the role. OpenProtein offers a competitive base salary and benefits.

Qualifications

• PhD with experience in ML/AI applied to biomolecules.
• Ability to operate independently with a track record of top publications.
• Experience with Python, Pytorch, and similar frameworks.
• Deep knowledge of neural network architectures for proteins.

Responsibilities

• Develop solutions for protein structure prediction and biomolecular problems.
• Lead research projects from ideation to deployment.
• Collaborate with stakeholders and manage communications.
• Present research findings to various audiences.

Skills

Machine Learning

Deep Learning

Bioinformatics

Python

Pytorch

Protein Engineering

Education

PhD in a relevant field

Tools

JAX

Bioinformatics Toolkit

Job description

USA or Singapore (Remote)

About OpenProtein.AI

At OpenProtein.AI, we are decoding the fundamental language of proteins to transform biological discovery and design. Our cloud-based SaaS platform enables biologists, bioinformaticians, and ML engineers across leading pharmaceutical companies, biotechs, and innovative startups to predict variant effects, optimize protein function, design novel proteins de novo, and accelerate design-build-test cycles with unprecedented data efficiency. We are building the next generation of protein foundation models, harnessing billions of years of evolution to break conventional scaling laws and deliver 20x superior design outcomes and 3x higher success rates with as few as tens of training examples. Join us in building the future of AIxBiology.

Responsibilities

• Develop deep learning and other algorithmic solutions for problems in protein structure prediction, sequence generation, function prediction, and other biomolecular areas
• Carry out research projects from ideation to experiment planning and execution to presentation and deployment of resulting solutions
• Lead collaborative research projects, including stakeholder management and communication, organising collaborators, etc.
• Present research findings internally and externally in the form of presentations, papers, blog posts, or similar
• Work with users and customers to ensure project success
• Contribute to identification, design, and implementation of new features in the OpenProtein.AI platform
• Stay up to date with the latest research, models, algorithms, and wet lab techniques

Requirements

• PhD with experience in ML/AI applied to biomolecules
• A demonstrated ability to operate independently and track record of publications in the top ML conferences or journals
• Experience with the typical engineering stack: Python and pytorch, jax, or similar deep learning frameworks
• Deep knowledge of neural networks for working on biomolecules, especially protein structure encoding and decoding architectures, protein language models, and diffusion models
• Experience with the general bioinformatics toolkit: homology search, sequence alignment algorithms, structure analysis tools, phylogenetics, PSSMs, HMMs, etc.
• Knowledge of wet lab techniques for general protein engineering, e.g., mutational scans, affinity selection assays, structure determination methods, biophysical characterization methods, etc.
• Collaborative mindset with the ability to prioritize high level goals

Nice to Haves

• Hands on experience with antibody engineering or enzyme engineering in a high throughput end-to-end setting
• Experience deploying machine learning models in production, including cluster and GPU management, and API design
• Experience with molecular dynamics
• Strong product and visual design sense
• Experience deploying and using LLMs and RAG solutions
• Experience with grant applications, forming industrial collaborations, or similar

Compensation

• Competitive base salary and equity
• Health and dental insurance