Machine Learning Intern - Protein Group
Zymo Research is looking for a dynamic individual to join their Protein R&D team. The qualified individual will lead and execute R&D projects for product development, optimization, and quality control using machine learning frameworks and AI models.
Responsibilities
- Design and conduct scientific experiments for product development, performance troubleshooting, and protocol optimization
- Analyze and interpret data to obtain insights into project progress
- Provide recommendations to the team leader on the next steps of the assigned projects
- Keep current with literature pertaining to the project and apply relevant findings to ongoing research projects
- Collaborate with other R&D team members to further multifaceted projects
- Work closely with internal subject matter experts, product managers, application, marketing, and manufacturing on technical details
- Project presentation to upper-level management, technical review committee, marketing, and sales organization
Skills
- Currently pursuing or recently graduated with a Bachelor's degree in Computational Biology, Bioinformatics, Computer Science, or related field
- Experience with machine learning frameworks and libraries, including TensorFlow, PyTorch, and Scikit-learn, with strong expertise in Python programming for model development and deployment
- Skilled in applying state-of-the-art deep learning and generative AI methods, including protein language models, for protein structure prediction and design
- Demonstrated success in designing, implementing, analyzing, and optimizing code, with ability to troubleshoot and debug complex workflows
- Excellent communication skills, both verbal and written
- Attention to detail and accuracy
- Familiarity with computational assessment of protein and antibody developability attributes is a plus
Benefits
- EAP Sessions
- Paid Sick Leave
- 401(K) plan
- Complimentary fruit, snacks, and beverages
- Complimentary catered lunches on Thursdays
- Complimentary EV Charging
Company Overview