Data Scientist Position in Arnaout Laboratory at UCSF
We are hiring a data scientist with mid-career skills and experience. Applications will be accepted on a rolling basis.
ABOUT. The Arnaout laboratory studies deep learning and other computational methods for biomedical imaging and related clinical data, with the goals of decreasing diagnostic error and developing and scaling novel phenotypes to drive precision medicine. UCSF is a top-10 medical center and a leader in cross-campus efforts to mine, harmonize, and analyze multi-modal clinical data for the University of California’s 15 million patients. The Arnaout laboratory is part of both the Bakar Computational Health Sciences Institute and the nationally ranked Department of Medicine. Projects focus on deep learning for medical imaging, and through collaborative work with intra- and inter-institutional partners, also involve the electronic health record, genetics, and other data types.
POSITION. The data scientist position offers an opportunity to participate in cutting-edge research with transformational impact to clinical and research medicine across a wide array of diseases, working with decades of high-quality medical data alongside clinical domain experts. The position also provides opportunities to publish, present at research conferences, and for professional advancement. Salary and benefits are set according to experience and to UCSF salary scales.
CONTACT. Applications should include a CV and a clear but brief letter of interest sent to rima (dot) arnaout (at) ucsf (dot) edu.
• A Masters, PhD or equivalent degree and/or experience in computer science, data science/analytics, or related field
• strong interpersonal, organizational, record-keeping, written and oral communication skills
• working with patient data in a HIPAA-compliant and morally and ethically responsible manner
• working closely with an interdisciplinary team including both medical and data science professionals
• working independently to complete assigned responsibilities
• strong motivation to apply pioneering breakthroughs to the practical, personalized everyday care of patients
• Experience in neural network design and optimization
• Fluency with Python (ideally using Pandas, Keras, Tensorflow/Theano, etc) and related programming languages, as well as data visualizations (ideally using d3.js, R, Matlab, pylab, seaborn, etc). Specific experience with computer vision projects, and with cloud computing/HPC is a plus
In addition to the above, the successful applicant will:
• be proficient in ‘cleaning’ data of several types (e.g. semi-structured text, images, vectors/matrices)
• be proficient in applying supervised and unsupervised machine learning and other computational techniques (including but not limited to neural networks, discriminant analysis, tree-based methods, boosting, random forests, and support vector machines, as well as [incremental] principal/independent component analysis, t-SNE, and data augmentation techniques) to imaging data
• be proficient in producing excellent data visualizations and analyses for machine learning results
• have a working knowledge of biology and human physiology, and/or a desire to learn relevant concepts