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Senior Data Scientist, Machine Learning or Computational Biology
1 month ago
Position: Senior Data Scientist, Machine Learning or Computational Biology
Location: Laguna Hills, CA
Company: Aureka Biotechnologies
Job Type: Full-Time
Reports To: VP
About Us:
Aureka Biotechnologies is an innovative startup focused on AI-driven antibody design to revolutionize drug development. We are a dynamic team dedicated to advancing scientific research and bringing transformative therapies to market. As a small but growing company, we offer a collaborative environment where every team member's contribution is crucial to our success.
Job Summary:
We are seeking a highly skilled and motivated Senior Data Scientist, Machine Learning or Computational Biology to join our research team. The ideal candidate will have extensive experience developing novel machine learning models and algorithms for data-driven generation of proteins and hone them through the deployment of our experimental platform.
Key Responsibilities:
- Pioneer new antibody design techniques, build robust data pipelines for antibody function and developability assays, and enhance Aureka’s statistical and machine learning models based on data insights.
- Advance and evaluate state of the art machine learning models for protein sequence, structure, and function, including but not limited to protein sequence design, structure prediction, complex prediction, and function learning.
- Use Aureka’s integrated data platform to devise models able to leverage measured labels “in-the-loop.”
- Develop production-quality code in a team setting and work with MLOps for deploying and training models at scale.
- Stay current with the latest scientific literature and technological advancements to bring innovative ideas and techniques to the team.
- Work closely with cross-functional teams, including computational biologists, engineers, business development, and project managers, to drive research and therapeutic projects forward.
Preferred Qualifications:
- Education: PhD in Computational Biology, Computer Science, or a related field with demonstrated experience working on scientific applications.
- Experience: 3+ years of experience with developing Machine Learning/Deep Learning methods to solve scientific problems, with a particular interest towards applications to protein modeling as well as adjacent fields such as genomics, chemistry, immunology, or physics
- Technical Skills:
- Experience developing, debugging, and applying models using modern deep learning frameworks.
- Proficiency in Python and experience analyzing data with Numpy/Scipy, R, or similar.
- Soft Skills:
- Excellent analytical and problem-solving skills.
- Strong organizational and time-management abilities.
- Effective communication skills, both written and verbal.
Nice to have:
- Foundational knowledge around probabilistic machine learning and optimization methods
- Practical experience developing deep generative models (e.g., autoregressive models, VAEs, Flows, Diffusion, EBMs etc.)
- Publications in major ML conferences or scientific journals that apply ML to problems in molecular biology, structural biology, or genetics, especially at the intersection of machine learning and proteins.
- Demonstrated experience developing software in a team setting.
- Experience with optimizing performant code.
Benefits:
- Competitive salary and equity options
- Comprehensive health, dental, and vision insurance
- Professional development opportunities
- Collaborative and inclusive company culture
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