Thermo Fisher Scientific Deep Learning Intern - R&D in South San Francisco, California
Summary of Internship
The Deep Learning Internship position provides an opportunity for STEM students who are currently enrolling a postgraduate program in computer science, electrical engineering, statistics, or similar, to get hands on experience working with scientists and engineers in a multidisciplinary and fast-paced environment. The intern will apply the state-of-the-art deep learning techniques to solved a complex and unexplored problem for improving the Ion Torrent Next-Generation Sequencing (NGS) platform. The position starts in June, paid working 40 hours per week through August. Opportunity exists for this position to continue through the academic year on a part-time basis to allow for class schedules.
Understand the fundamentals on the sequencing technology
Explore the problem and proposal a data-driven solution to tackle the problem
Develop a pipeline that converts the idea from abstract to practice
Validate the pipeline and demonstrate the feasibility of the approach from massive amount of data in real world
Skills and Abilities
Ability to work independently and as a member of a cross-functional team
Solid backgrounds on machine learning, deep learning, statistics
Proficiency in Python, R and/or C+* Hands on experiences in deep learning software such as TensorFlow, Keras, MXNet
Familiar with CUDA is a plus
M.S. or PH.D. student in computer science, electrical engineering, bioinformatics, statistics, data science, applied mathematics, or similar discipline
Strong knowledge about modern machine learning techniques and expertise in quantitative analysis
If you are an individual with a disability who requires reasonable accommodation to complete any part of our application process, click here at https://jobs.thermofisher.com/page/show/eeo-affirmative-action-statement#accessibility for further assistance.
Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.