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: http://drexeleesi.com
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.)
