Scientist I, Machine Learning

Disability Solutions - Boston, MA

Full-time - Mid Level

Boston, MA

About the position

The Scientist I, Machine Learning plays a crucial role in the Cancer Genomics Research group at FMI by contributing to the research, implementation, and validation of computational methods. This position focuses on developing machine learning algorithms and data pipelines that analyze histopathology images alongside genomic sequencing data and clinical outcomes. The role involves investigating novel biomarker signatures, discovering new cancer genomics findings, and enhancing operational pipelines through data science partnerships.

Responsibilities

• Perform machine learning and deep learning on large-scale structured and unstructured datasets to extract biological insights.
• Develop data pipelines, infrastructure, and computational tools for large-scale image analysis.
• Provide scientific expertise and support for internal teams and external collaborators.
• Conduct novel cancer genomics research using both public and internal datasets.
• Prepare reports and presentations to communicate results in group meetings.
• Present novel findings via abstracts or manuscripts.
• Other duties as assigned.

Requirements

• Bachelor's Degree in Computer Science, Bioinformatics, Computational Biology, Engineering, or other similar quantitative discipline and 3+ years of work experience in relevant field; OR Master's Degree in the same fields and 2+ years of experience in relevant field.
• Strong experience with deep learning methods and frameworks (Tensorflow, PyTorch, etc.) and a strong understanding of their mathematical foundations.
• Intermediate proficiency or higher in object-oriented programming with Python, Java, or C++.
• Experience with traditional machine learning methods and packages (e.g. sklearn) and a strong understanding of their mathematical foundations.
• Experience with distributed processing and computation (Spark, Horovod, job scheduling, etc.) for large-scale datasets.
• Familiarity with using cloud compute providers (AWS, GCP, etc.).
• Strong communication and teamwork skills to work effectively in a flexible, cross-functional environment.
• Understanding of HIPAA and the importance of patient data privacy.

Nice-to-haves

• Ph.D. degree in Computer Science, Bioinformatics, Computational Biology, Engineering, or other similar quantitative discipline.
• Knowledge of cancer biology and cancer genomics.
• Experience with histopathology analysis.
• Previous authorship/co-authorship of relevant work.