Computational Associate
$41,933–$60,341 year
On-siteBoston, Massachusetts, United States
Job Summary
Develop and apply machine learning and computer vision models for digital pathology and whole-slide image analysis. Analyze genomic, transcriptomic, epigenomic, and spatial biology datasets. Build computational workflows that integrate pathology images, molecular data, and clinical outcomes. Support biomarker discovery and prognostic model development through multimodal data analysis. Collaborate with a multidisciplinary team to contribute to scientific presentations, manuscripts, and publications. Provide direct assistance with experimental studies and perform administrative tasks such as data collection, documentation, and database updates.
Required Qualifications
- Bachelor's Degree Computational Biology required
- Bachelor's Degree Related Field of Study required
- Experience as attained through education 0-1 year required
- Understanding of human pathophysiology, hematologic function, pregnancy physiology and related fields of study
- Understanding of mathematical modeling, including dynamical systems, statistical analysis, and computational methods
- Ability to work collaboratively as part of a team and with supervision from team members
- Ability to work productively with scientists and clinicians at all levels
- Works in an organized manner with the ability to follow instructions, processes and timelines
- Strong computer skills, including accurate data entry
Desired Qualifications
- Bachelor's or Master's degree in Computer Science, Bioinformatics, Computational Biology, Biomedical Engineering, Statistics, Data Science, Genetics, Epidemiology, or a related quantitative field
- Proficiency in Python and/or R programming
- Experience with or strong interest in machine learning, artificial intelligence, bioinformatics, computational biology, or biomedical data science
- Experience with digital pathology, whole-slide image analysis, computer vision, or medical imaging applications
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow
- Experience analyzing genomics, RNA sequencing, spatial transcriptomics, single-cell, or epigenomic datasets
- Experience integrating and interpreting multiple biological data modalities across complex research projects
- Strong analytical, organizational, communication, and collaboration skills
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