Computational Biologist - Genomics

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

Benefits offered by this job

Stock options

Job summary

Waypoint Bio seeks a highly motivated computational biologist to work across our R&D program. You will apply deep learning and software engineering to fluorescence microscopy data, guiding the design of cell therapies for solid tumors and collaborating with experimental biologists to push the platform forward.

You will join a collaborative, interdisciplinary team in a well-funded biotech startup, focusing on innovative methods and scalable computational pipelines to accelerate cancer therapies.

Qualifications

• PhD or equivalent in bioinformatics, computational biology, CS, data science, AI, or statistics.
• Familiarity with molecular and cellular biology.
• Proficiency with Python/R and libraries (numpy, scikit-learn, pandas, pytorch).
• Experience with ML, esp. deep learning.
• Ability to optimize code for speed and efficiency.
• Familiarity with software development practices (version control, file management, organization).
• Ability to learn quickly, prioritize multiple tasks in a fast-paced environment.
• Rigorous understanding of scientific and statistical practices (experimental design, hypothesis testing).
• Clear and precise technical communication.

Responsibilities

• Analyze and interpret spatial biology data from Waypoint’s platform to evaluate cancer therapies.
• Develop computational methods to design and filter thousands of novel candidate cancer therapies (modeling/designing cells, pathways, proteins).
• Develop, maintain, and run pipelines for fluorescence microscopy image analysis and data processing.
• Develop and maintain compute infrastructure to automate and scale our methods.
• Collaborate with experimental scientists to innovate across disciplinary boundaries.
• Collaborate on joint projects and shared code bases with other computational scientists.

Skills

Machine learning

Computational biology

Strong communication

Problem solving

Independent learner

Education

PhD or equivalent in bioinformatics, computational biology, computer science, data science, AI, or statistics

Tools

Python

R

numpy

scikit-learn

pandas

pytorch

Job description

• 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:

We are seeking a highly motivated, innovative, and rigorous computational biologist to work across the breadth of our research and development program. The ideal candidate will have deep knowledge of computational biology 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. They will push the limits of what can be inferred from our growing dataset of fluorescence microscopy images from cancer tissue samples, while collaborating with experimental biologists to design and develop further improvements to the spatial biology platform. Our high-throughput screening creates a unique opportunity for inventive minds to design/test novel ideas for better-engineered cell therapies. 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:

• Analyze and interpret spatial biology data from Waypoint’s spatial pooled screening platform to evaluate cancer therapies
• Develop computational methods to design and filter thousands of novel candidate cancer therapies, e.g. by modeling and designing cells, pathways, and proteins
• Develop, maintain, and run pipelines for fluorescence microscopy image analysis and data processing
• Develop and maintain compute infrastructure to automate and scale our methods
• Collaborate with experimental scientists to innovate across disciplinary boundaries
• Collaborate on joint projects and shared code bases with other computational scientists

Required Qualifications

• PhD or equivalent research experience in bioinformatics, computational biology, computer science, data science, artificial intelligence, statistics, or a related quantitative field
• 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
• Familiarity with best practices for software development (version control, file management, organization)
• Ability to learn quickly, prioritize multiple tasks in accordance with changing responsibilities, and work in a fast-paced environment
• Rigorous understanding of scientific and statistical practices (e.g. experimental design, hypothesis testing)
• 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