The successful applicant will work with the PI under direct supervision in designing, testing, and validating algorithms and models for data analysis, providing data visualization of analyzed results, for various ongoing life sciences projects. The successful applicant will use bioinformatics concepts, and assist in additional analyses as needed to achieve research objectives.
• Specific job responsibilities:
o Utilize standard software tools such as Tensorflow, Keras, and Theano, in Python to develop and implement deep-learning and related methods to analyze cardiovascular imaging and associated metadata.
o Design, develop, debug and utilize computational techniques (including but not limited to neural networks, discriminant analysis, tree-based methods, boosting, random forests, and support vector machines) to imaging data and associated clinical metadata for tasks such as classification and regression.
o Utilize existing algorithms, techniques, and statistical methodologies (such as [incremental] principal/independent component analysis, t-SNE, and data augmentation techniques) to conduct moderately complex data analysis of machine learning results.
o Develop and maintain architecture for data storage (using tools including but not limited to SQL)
o Develop and/or implement Python-based code for mining and 'cleaning' data of several types (e.g. semi-structured text, images, vectors/matrices)
• REQUIRED Qualifications:
o Bachelor's degree in biological science, computer science / programming, or related area AND 10 years of data science experience; OR
o Master’s degree in bioengineering, computer science, or related computational field AND 10 years of equivalent data science experience
o PhD in bioengineering, computer science, or related computational field or 10 years of equivalent data science experience.
o Working knowledge of bioinformatics methods and data structures.
o Working knowledge of databases.
o Fluency in Python.
o Team player with interpersonal skills in order to work with both technical and non- technical personnel at various levels in the organization.
o Ability to communicate technical information in a clear and concise manner.
o Self-motivated, able to learn quickly, meet deadlines and demonstrate strong organizational and problem solving skills.
o Knowledge of application and data security concepts.
o Expertise in machine learning techniques such as convolutional neural networks, recursive neural networks, LSTMs, random forests
o Interest in applying computational analysis to life sciences data
o Demonstrate high integrity and professionalism to work with patient data in a HIPAA- compliant and morally and ethically responsible manner
• PREFERRED Qualifications:
o Working knowledge of R and bioinformatics pipelines
o Working knowledge of applications programming and web development.
o Working project management skills.
o Working knowledge of modern biology and applicable field of research.
o Industry experience in data science, specifically with cutting-edge machine learning approaches to data analysis.(1 year minimum; 2-3 years preferred)
UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence.
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.
Please apply online at https://aprecruit.ucsf.edu/apply/JPF02338