Senior Computational Biologist, Machine Learning

About the Job

The Senior Computational Biologist, 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.
• Lead efforts to 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.

Qualifications

Basic Qualifications

• Bachelor’s Degree and 6+ years of research experience in the life sciences industry; OR,
• Master’s Degree and 5+ years of research experience in the life sciences industry; OR,
• PhD and 3+ years of research experience in the life sciences industry

Preferred Qualifications

• 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
• Expertise in developing and applying both classical statistical and machine learning algorithms and pipelines using relevant tools in R or python
• Experience in cloud-based, high-performance UNIX-compute environments (e.g., AWS, Apache Spark, very large datasets)
• Strong understanding of molecular biology, genomics and epigenetics in cancer
• Demonstrated ability to:
  • work independently in a multidisciplinary, dynamic, and results-oriented team
  • present data to multidisciplinary colleagues in a clear manner
• Excellent teamwork, time management and organizational skills
• Understanding of HIPAA and importance of privacy of patient data
• Commitment to FMI's values: passion, patients, innovation, and collaboration