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Computational Biologist II, Machine Learning

  • 400 Summer Street, Boston, Massachusetts, United States
  • Full Time

About the Job

The Computational Biologist II, Machine Learning will work as part of a new product team, focused on improving blood-based cancer diagnostic capabilities in areas such as cancer detection, minimum residual disease, and other related applications. This team is comprised of talent from across the Roche ecosystem, including Roche Diagnostics, Roche Pharma and Foundation Medicine, operating as a single unit.

The Computational Biologist II, Machine Learning contributes to research, implementation, and validation of computational methods for FMI’s Research and Cancer Genomics Research groups. The position’s contributions focus on feasibility analyses of novel diagnostic methods and identification of biomarker signatures from genomic and epigenomic data.

Key Responsibilities

  • Work in an interdisciplinary team of molecular biologists, computational biologists, and data scientists focused on developing innovative approaches in tumor detection and oncology biomarkers using NGS in blood and tissue specimens from cancer patients.
  • Analyze raw data from novel molecular biology and instrumentation platforms to provide insights into effectiveness and development of approaches.
  • Identify and analyze novel biological measurements and signals to develop and optimize strategies for detection of tumor and improvement of clinical biomarkers.
  • Monitor and evaluate analytical aspects of new and emerging technologies.
  • Present scientific and technical data to colleagues in a clear and cohesive manner.
  • Other duties as assigned.


Basic Qualifications

  • Bachelor’s Degree and 5+ years of research experience in the life sciences industry; OR,
  • Master’s Degree and 3+ years of research experience in the life sciences industry; OR,
  • PhD and 2+ years of research experience in the life sciences industry

Preferred Qualifications

  • Significant experience with state-of-the-art methods and tools in Machine Learning and Deep Learning including familiarity with toolkits like scikit-learn, tensorflow, pytorch, and mlr3. Ideally brings a good foundational understanding of topics like feature engineering, managing overfitting risks, applicability of various algorithms and model architectures to different problem classes and feature spaces. 
  • Significant experience applying computational biology and data-science methods to “big” genomic and epigenomic data in cancer, including identifying and extracting novel signals and managing very large feature sets 
  • Strong expertise in python or R including comfort in building one-off analyses and in developing tools and pipelines that are shared among others. Some exposure to source-code management and team programing is preferred. 
  • Experience in cloud-based, high-performance UNIX-compute environments for big-data, e.g. grid computing, cloud-based object storage, workflow tooling, SQL, very large datasets 
  • Understanding of molecular biology, genomics and epigenetics in cancer. Understanding of the impacts of lab molecular biology and NGS processes on data quality is preferred. 
  • Demonstrated ability to: 
    • Work independently and collaboratively in a multidisciplinary, dynamic, and results-oriented team environment 
    • Present data to multidisciplinary colleagues in a clear manner 
  • Excellent teamwork, time management and organizational skills. We are looking for a collaborative colleague and strong team-player. 
  • Understanding of HIPAA and importance of privacy of patient data 
  • Commitment to FMI's values: passion, patients, innovation, and collaboration.


About Foundation Medicine

Foundation Medicine began with an idea—to simplify the complex nature of cancer genomics, bringing cutting-edge science and technology to everyday cancer care. Our approach generates insights that help doctors match patients to more treatment options and helps accelerate the development of new therapies. Foundation Medicine is the culmination of talented people coming together to realize an important vision, and the work we do every day impacts real lives.

Confidence, or the belief that we need to check every box before applying for a job, can sometimes hold us back from going after a role that inspires us. At Foundation Medicine there's no such thing as the 'perfect' applicant, and our company is a place where every employee can make an impact and continue to grow whatever background they may have or path they may have taken. So, as long as you meet the basic qualifications for a role, please apply if you see a position that would make you excited to come into Foundation Medicine every day and help us transform cancer care.

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Internal applicants, please use your FMI email address.

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Foundation Medicine is proud to be an Equal Opportunity and Affirmative Action employer and considers all qualified applicants for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity, ancestry, age, or national origin. Further, qualified applicants will not be discriminated against on the basis of disability or protected veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also FMI’s EEO Statement and EEO is the Law and Supplement. If you have a disability or special need that requires accommodation, please let us know by completing this form.  (EOE/AAP Employer)

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