Senior Data Scientist, Machine Learning

Data Sciences

Position Summary

We are seeking an innovative, collaborative and accomplished data scientist to work on new applications of machine learning and deep learning to a variety of genomics projects in the field of immuno-oncology and autoimmune diseases. The individual will work in a team of both genomics experts and machine learning experts to develop new algorithms and innovative strategies for the analysis of very large amounts of single cell RNAseq data in the context of drug discovery.

Responsibilities/Requirements

The successful candidate will join a dynamic and growing team of scientists using cutting edge genomics techniques and single cell sequencing for the discovery of new drug targets. Primary responsibilities will be to:

  • Develop or apply new tools, algorithms, machine learning or data mining techniques for the integrative analysis of large single cell RNAseq datasets.
  • Train and evaluate machine learning models to answer genomics questions, improve Celsius’ platform.
  • Evaluate fits, error metrics and model diagnostics to assess and improve model performance.
  • Participate in the development of a platform for genomics-based target discovery.
  • Generate meaningful biological hypothesis from genomics data.

Qualifications

  • A Ph.D. in Bioinformatics, Computer Science, Biology, Genetics or equivalent scientific discipline, and a minimum of five years of experience in computational biology or data science required and a specialization in machine learning or deep learning.
  • Strong scientific background and publication record with proven high levels of performance.
  • Ability to innovate, develop and apply new tools for the integrative analysis and visualization of multiple high-dimensional genomics datasets.
  • Proficiency with R, Python or other scripting language for statistical computing (strong ability in C++ a plus).
  • Strong experience with machine learning algorithms and data mining methods, such as: deep learning, Bayesian modeling, time series analysis, latent variable models, and more.
  • Experience with TensorFlow, Keras, PyTorch, or similar framework.
  • A background in cancer biology and/or single cell genomics and/or immunology is a plus.
  • Experience with cloud computing is a plus.
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