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Data Scientist II, Pathology BWH

Data Scientist II, Pathology BWH
 - (3213248)
The Microbiome AI/Deep Learning Lab in the Massachusetts Host-Microbiome Center and Division of Computational Pathology at Brigham and Women’s Hospital/Harvard Medical School is seeking a computational scientist with experience in machine learning. You will develop, deploy, and apply machine learning approaches, with a special emphasis on deep learning, to a variety of microbiology data sources. Applications will include forecasting microbial population dynamics in the gut, predicting impact of the microbiome on host phenotype, tracking infections in human populations, elucidating microbial metabolism, and discovering functions of uncharacterized microbial metabolites and proteins. An important component of the position will also include engagement with the broader research community to identify new application areas.
Applicants should have a high level of interest in:
  • Applying new deep learning technologies to biomedical problems.
  • Advancing knowledge of the microbiome and its role in human health and disease.
  • Having your work make a direct impact on healthcare outcomes.
  • Working on an interdisciplinary team and collaborating with computational, wet lab and clinical scientists.
  • Engaging with the broader research community to advance applications of AI/deep learning for the microbiome.
About the environment: The Microbiome AI/Deep Learning Lab is a newly established initiative within the Massachusetts Host-Microbiome Center (MHMC) and the Division of Computational Pathology (DCP) at Brigham and Women’s Hospital (BWH)/Harvard Medical School (HMS). With recent funding from the Massachusetts Life Sciences Center, the Lab is building a state-of-the-art compute cluster with extensive GPU and CPU nodes, with the objective of making advanced deep learning technologies broadly available to microbiome researchers. The MHMC is a research and core facility that has worked with 100+ groups in the US and internationally to promote understanding of host-microbiome interactions in health and disease, emphasizing a focus on function to define causative effects of the microbiota and to harness this knowledge in developing new therapies, diagnostics and further commercial applications. The DCP is a research division with a broad mandate to develop and apply advanced computational methods for furthering the understanding, diagnosis and treatment of human diseases. BWH is an HMS affiliated teaching hospital, adjacent to the HMS main quad, and the second largest non-university recipient of NIH research funding.
  • Develop machine learning approaches, with a special emphasis on deep learning, for a variety of microbiology data sources, including next generation sequencing and metabolomic data.
  • Deploy computational pipelines on local workstations and on high performance CPU and GPU clusters.
  • Analyze datasets and produce visualizations and written reports, including contributing to scientific publications and grant applications.
  • Manage large datasets produced at BWH or by collaborators, including developing databases.
  • Engage with BWH researchers and conduct broader outreach, with the goal of increasing application of machine learning technologies for the microbiome.
  • Other duties as assigned.
  • PhD in Computational Biology, Computer Science, Physics, Statistics, Quantitative Microbial Genetics, Quantitative Ecology, or related quantitative discipline, OR MA/MS in a relevant discipline with 5+ years experience.
  • Experience in machine learning applications demonstrated through authorship on scientific publications.
  • 3+ years minimum Python programming experience.
  • 3+ years minimum experience working in high-performance computing environments.
  • Experience with bioinformatics methods and pipelines for next generation sequencing data analysis.
  • Experience with organizing and managing large multi-omics datasets.
  • Strong verbal and written communication, and interpersonal skills.
  • Experience with microbiology/microbiome applications and metabolic modeling tools is highly desired.
  • Experience with deep learning and PyTorch is highly desired.
  • Must be capable of contributing within an interdisciplinary team, exhibit a high level of initiative, and have an eagerness to learn new technologies.
  • Ability to manage entire projects in a research environment, from design to implementation, and interpretation of final results.
  • Must possess advanced knowledge of machine learning, including model development, training, testing and deploying.
  • Demonstrated ability to develop and implement novel computational approaches for analyzing complex biomedical datasets including next generation sequencing data.
  • Demonstrated ability to manage large and complex biomedical datasets, using tools such as databases.
  • Experience working with microbiology or microbiome datasets is highly desired.
  • Excellent written and verbal communication skills with demonstrated ability to communicate complex results to both technical and non-technical audiences, through publications and presentations.
  • Ability to implement machine learning methods in Python; experience with deep learning and using PyTorch is highly desired.
  • Knowledge of software engineering best practices, including source code management/control (e.g., Git) and containerizer approaches.
  • Experience with high-performance computing environments, including scheduling systems, e.g., LSF or SLURM.
  • Ability to multitask and prioritize work, to achieve desired goals and deliverables.
  • Excellent interpersonal skills to effectively communicate with multidisciplinary teams including staff at all levels of the organization
  • Ability to share expertise, coach, and give general direction to others of different skill sets, backgrounds and levels.
  • Ability to lead outreach efforts within and external to the organization, to further the goal of the project.
EEO Statement
Brigham and Women’s Hospital is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, national origin, sexual orientation, protected veteran status, or on the basis of disability.
Primary Location MA-Boston-BWH Longwood Medical Area
Work Locations BWH Longwood Medical Area 75 Francis Street  Boston 02115
Job Data/Analytics
Organization Brigham & Women's Hospital(BWH)
Schedule Full-time
Standard Hours 40
Shift Day Job
Employee Status Regular
Recruiting Department BWH Pathology