Computational Biologist

3 days left

Employer
Genuity Science
Location
Boston, Massachusetts, US
Salary
Competitive
Posted
Jul 12, 2021
Closes
Aug 03, 2021
Ref
2336868927
Discipline
Statistics
Employment Type
Full time
Salary Type
Salary
Job Description
The Advanced Artificial Intelligence Research Laboratory at Genuity Science is seeking a highly motivated Computational Biologist to help pioneer the use of AI/ML in the biomedical sciences. The candidate will work on data generated from secondary/tertiary analysis pipelines and use AI/ML, probabilistic programming, and other statistical genomics approaches to analyze various large-scale omics data sets to better understand disease etiology, identify novel drug targets, and discover biomarkers for use in precision medicine.

Given the multi-disciplinary nature of the position, strong collaboration and communication skills are expected.

Essential Qualifications:
  • M.Sc. in Engineering, Computational Statistics, Computer Science, Biostatistics, Bioinformatics, or related field with a minimum of 2-years of related industry and/or academic experience
  • Experience in machine learning, deep learning, statistical methodology, predictive modeling and algorithm development
  • Familiar with NGS data analysis, using common bioinformatics tools (BWA, STAR, Picard, GATK etc.), and knowledge of publicly available genomics databases (i.e. ENCODE, GEO, TCGA, CCLA)
  • Advanced programming skills with fluency in at least Python and/or R, with extensive experience using modern machine learning and deep learning libraries (TensorFlow, PyTorch, Edward, sklearn, caret, etc.)
  • Proven ability to design and code production grade machine AI/ML applications, along with a strong ability to visualize ‘big data'
  • Ability to work on high-performance computing system and manage cloud computing environments (e.g. AWS) with experience working with GPUs
  • Strong communication and presentation skills with the ability to translate and communicate results to individuals of diverse backgrounds

Preferred Qualifications:
  • Ph.D. and postdoctoral training in Engineering, Computational Statistics, Computer Science, Biostatistics, Bioinformatics, or another related field
  • Understanding of modern genomics analysis including RNA-seq, single cell RNA-seq, DNA methylation, variant analysis, etc.
  • Development and application of digital pathology and natural language processing algorithms
  • Working knowledge of biology (oncology, immunology, autoimmunity, etc.) and experience in drug target identification
  • Up-to-date knowledge of the fast-moving AI/ML literature

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