Computational Biologist - Protein Design

Waypoint Bio; New York (NY); On-site; USD 110,000 - 150,000; Full time

Job summary

Waypoint Bio in New York, NY is seeking a highly motivated computational biologist to design thousands of synthetic protein sequences using in silico folding models and a high-throughput spatial pooled screening platform. You will apply machine learning and robust software engineering to evaluate candidates for in vitro and in vivo testing.

The ideal candidate will have deep knowledge of protein folding, strong ML/AI skills, and the ability to work independently and collaboratively in a

Qualifications

• PhD or equivalent research experience in computational biology, bioinformatics, computer science, data science, AI/ML, statistics, structural biology, or a related quantitative field.
• Experience with protein structure design.
• Understanding of the fundamentals of molecular and cellular biology.
• Proficiency with scientific computing in Python/R and relevant libraries (e.g. numpy, scikit-learn, pandas, pytorch).
• Experience with machine learning, esp. deep learning.
• Ability to optimize code for speed and efficiency.
• Ability to learn quickly, prioritize multiple tasks in accordance with changing responsibilities, and work in a fast-paced environment.
• Clear and precise technical communication.

Responsibilities

• Design thousands of novel synthetic proteins that accomplish specific goals using in silico folding models and other technologies.
• Build computational methods to evaluate potential protein candidates to filter those worth testing in vitro and in vivo.
• Connect structure to function. Mine our growing dataset of spatially resolved, in vivo screening data to learn what structural features actually drive behavior in a tumor.
• Collaborate with experimental biologists to design the screens to test designs, and to translate what comes back into the next hypothesis.

Skills

Python

R

Machine learning

Deep learning

Code optimization

Technical communication

Education

PhD or equivalent research experience in computational biology, bioinformatics, computer science, data science, AI/ML, statistics, structural biology, or a related quantitative field

Tools

NumPy

scikit-learn

pandas

PyTorch

Job description

• Full-time position
• 430 E 29th St, New York, NY
• Competitive compensation: $110,000-150,000 Salary, Benefits, plus Stock Options in a well-funded startup

About Waypoint Bio:

Waypoint Bio a venture-backed biotech startup innovating in spatial and computational biology and their application to advancing cancer therapies. Our leading focus is the development of next generation of cell therapies for solid tumors. Our proprietary platform overcomes a major obstacle — the tradeoff between that with fast but inaccurate in vitro and more accurate but slow and expensive in vivo approaches — that holds back traditional cell therapy preclinical development. Combining spatial pooled screening, in silico engineering, and machine learning, we obtain both depth and breadth when screening cell therapy candidates: speed without compromising on in vivo accuracy. Our team is highly collaborative, interdisciplinary, and committed to developing breakthrough therapies to benefit patients’ lives.

Position Summary:

A huge part of engineering better cell therapy treatments for solid tumors will be designing synthetic proteins that solve multiple challenges from the tumor microenvironment, and doing so in a programmable way. We are seeking a highly motivated, innovative, and rigorous computational biologist to design thousands of innovative synthetic & chimeric protein sequences with unique functionalities. Our high-throughput spatial pooled screening platform offers a unique opportunity to evaluate all these novel protein design ideas with multi-parametric readouts.

The ideal candidate will have deep knowledge of protein folding and machine learning, excellent software engineering skills to put that knowledge into practice, the ability to solve problems independently and collaboratively, and a passion for learning and developing new skills. We seek broadly knowledgeable and creative thinkers who bring together ideas from disparate areas of the biological and computational sciences to make the most of this opportunity, as well as opportunities for our platform beyond cell therapies.

The role reports directly to our Chief Technology Officer, Patrick Kaifosh.

Responsibilities:

• Design thousands of novel synthetic proteins that accomplish specific using in silico folding models and other technologies
• Build computational methods to evaluate potential protein candidates to filter those worth testing in vitro and in vivo
• Connect structure to function. Mine our growing dataset of spatially resolved, in vivo screening data to learn what structural features actually drive behavior in a tumor - and turn that into better priors for the next design round
• Collaborate with experimental biologists to design the screens to test designs, and to translate what comes back into the next hypothesis

Required Qualifications

• PhD or equivalent research experience in computational biology, bioinformatics, computer science, data science, AI/ML, statistics, structural biology, or a related quantitative field
• Experience with protein structure design
• Understanding of the fundamentals of molecular and cellular biology
• Proficiency with scientific computing in Python/R and relevant libraries (e.g. numpy, scikit-learn, pandas, pytorch)
• Experience with machine learning, esp. deep learning
• Ability to optimize code for speed and efficiency
• Ability to learn quickly, prioritize multiple tasks in accordance with changing responsibilities, and work in a fast-paced environment
• Clear and precise technical communication

Why this might be a great role for you:

• You are interested in machine learning and are looking for a meaningful way to apply it.
• You enjoy working in a fast-paced environment with exciting challenges and learning opportunities.
• You want to work in a small well-funded startup with a tight knit multidisciplinary team.
• You want to use your skills to help develop new cancer treatments