Job:PhD Position to Develop Machine Learning Methods for Microbiome Analysis
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9 months ago
glr26 • 0

Looking for a highly motivated PhD student for Computational Biology research, with an algorithm development focus. The Ecological and Evolutionary Signal-processing (EESI) and Informatics lab is doing a restart from the pandemic and will be composed of a dynamic, interdisciplinary team. The project that the student will support will be designing semi-supervised clustering and classification techniques. Also, there is an emphasis on algorithm efficiency analysis and optimization — so great programming skills are required. In addition, the student will be investigating deep learning architectures to improve DNA/RNA identification and microbiome analysis. Former lab members have gone on to work in prestigious data science jobs in industry, medical research labs, and one at a tenured position at a university. A PhD in EESI will easily lead to a fruitful career in data science development and research at top notch institutions.

More info:

What’s important to the EESI Lab:

  • Curiosity — we are passionate about the possibilities of personalized medicine via microbiome manipulation and individual genomics
  • Responsibility — We have an obligation to the community to conduct ethical research and communicate clearly with stakeholders
  • Agility — flexibility and a desire to be nimble, smart, and effective
  • Follow-through — we’re building a diverse team in a multidisciplinary environment

Position Requirements:

  • B.S. in Computer Engineering, Electrical Engineering, Computer Science, Biomedical Engineering, or related discipline like Physics/Math
  • Problem-focused
  • Independent and able to drive tasks to completion
  • Proficiency in Python Basic UNIX/Linux knowledge but willing to learn
  • comfortable with the Linux command line interface (pipelines, sed, grep, awk, etc.)
  • some familiarity with command line development tools: make, cmake, git

Preferred Skills:

  • Masters of Science in a related field
  • Experience with PyTorch/Tensorflow/Keras and/or machine learning implementations
  • Machine Learning theory
  • Experience with programming (C/C++)
  • Experience with distributed computer architectures and working with containers
  • Knowledge of (GP)GPU programming and CUDA
  • Familiarity with building open source software (GNU-style configure and make, etc.)
microbiome machine-learning • 590 views

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