PhD Positions at the Cross section of Machine Learning and the Microbiome Full-time

Looking for highly motivated PhD students 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.

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.)

Tagged as: Computer Science, Engineering, Life Sciences, Mathematics