Computational Statistician – Cambridge, MA 02142

The Advanced Artificial Intelligence Research Laboratory at WuXi NextCODE is seeking a highly motivated statistician, engineer, or data scientist to help pioneer the use of machine-learning/deep-learning in genomics. The candidate will use machine-learning/deep-learning and statistical approaches to analyze various genomics data sets to better understand disease etiology, identify novel drug targets, and discover biomarkers to be used in precision medicine.

Minimum Qualifications:

  • M.S. in Engineering, Bioinformatics, Statistics, Computer Science, or another related field with a minimum of 2-years of related industry or academic experience

-or-

  • Ph.D. in Engineering, Bioinformatics, Statistics, Computer Science, or another related field

  • Basic knowledge of statistics (both Bayesian and non-Bayesian), machine learning, and data analysis

  • Programming experience in at least one language (Python, R, MATLAB, C++) with knowledge of machine learning libraries

  • Strong communication and presentation skills with the ability to translate and communicate complex results to individuals of diverse backgrounds

  • Team oriented and highly collaborative (with both our academic and industry partners) with strong organizational and communication skills

Preferred Qualifications:

  • M.S. in Engineering, Bioinformatics, Statistics, Computer Science, or another related field with 6-years of related industry or academic experience

-or-

  • Ph.D. in Engineering, Bioinformatics, Statistics, Computer Science, or another related field with 3-years of related industry or academic experience

  • Advanced programming skills with fluency in at least Python 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 learning and deep learning applications, along with a strong ability to visualize ‘big-data’

  • Ability to manage cloud computing environments (e.g. AWS) with experience working with GPUs

  • Understanding of modern genomics analysis including RNA-seq, single cell RNA-seq, DNA methylation, variant analysis, etc.

  • Working knowledge of biology (oncology, immunology, autoimmunity, etc.) and target identification

  • Knowledge of publicly available genomics databases (i.e. ENCODE, GEO, TCGA, CCLA)

  • Up-to-date knowledge of the fast moving machine-learning/deep-learning literature

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