Research Technician

The Research Technician will support computational biology and machine learning research in the Yang Lab. The primary responsibilities will include fine-tuning diffusion-based generative models for biological structure prediction and design, developing and maintaining computational pipelines, and leading a defined research project focused on applying deep learning methods to biomolecular modeling. The position will involve implementing and evaluating model fine-tuning strategies, running large-scale computational experiments on high-performance computing infrastructure, analyzing model outputs, and contributing to reproducible research workflows. The Research Technician will also help coordinate project milestones, document methods and results, and work closely with lab members to integrate computational approaches with ongoing biological research questions.

Job Description:

• Develop, fine-tune, and evaluate diffusion-based and other machine learning models for biomolecular structure prediction and design. Estimated time: 35%
• Build, maintain, and document computational pipelines for model training, inference, data processing, benchmarking, and analysis. Estimated time: 25%
• Run and monitor large-scale computational experiments on high-performance computing systems, including preparing jobs, troubleshooting failures, organizing outputs, and maintaining reproducible workflows. Estimated time: 15%
• Analyze model outputs and biological structure data, summarize results, generate figures or reports, and communicate findings to the Principal Investigator and lab members. Estimated time: 15%
• Coordinate progress on assigned research milestones, maintain organized records of methods and results, and contribute to lab meetings, manuscript preparation, and related project documentation. Estimated time: 10%

The hourly rate for the position is $22

Job Requirements:

• High School diploma, BS preferred
• Experience in Computer coding, Machine Learning, and Biology is strongly preferred.

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").