Open Positions

Graduate Students and Postdocs

We are looking for graduate students and postdoctoral fellows who are excited about applying computational techniques including neural networks, computer vision, algorithms, 3d modeling, and/or signal processing, to ask and answer important questions in computational imaging for clinical care. Candidates will be in a program for (grad students) or will have obtained (postdocs) a PhD degree in computer science, graphics, engineering, applied mathematics, physics, or related field. Candidates should be fluent in Python, including tools such as Tensorflow, Keras, or PyTorch; Pandas; Scikit; as well as other tools (e.g. d3.js, R, Matlab, pylab, seaborn, etc). Familiarity with computing in the cloud/on HPC is a plus. Graduate students must be enrolled in UCSF's Graduate Program for Biomedical Informatics (BMI). or to the UCSF UC Berkeley Joint Program in Computational Precision Health (CPH)

Data Engineer

APPLY. We are looking for a data engineer to who is excited about helping us scale data mining, annotation, transfer, and computation on terabytes of multimodal imaging data and associated clinical metadata in an academic medical setting. The candidate will learn how to access and connect data from several institutional databases and will interact with engineers and physicians. They will have experience with local, hybrid, and cloud computing/HPC; data containerization strategies (e.g. Docker, Kubernetes), as well as basic databases (e.g., SQL/noSQL strategies, graphs). They will create web-apps, visualizations, executables to share our research and our code. Research projects will include how to scale datamining in the clinical setting; how to crowdsource and gain consensus on clinical labeling; how to maintain and disseminate sustainable code in clinical settings. They will have a Masters, PhD or equivalent degree and/or experience in computer science, applied mathematics, bioengineering, or related field.

Data Scientist

APPLY. We are looking data scientists to help analyze medical imaging and related data types, with the goal of decreasing diagnostic error in imaging and discovering and validating new image-based phenotypes, including putting new findings in clinical and biostatistical context. The successful candidate has a master's degree or equivalent experience in computer science, process engineering, mechanical engineering and 3D modeling, bioengineering, data science/analytics, applied math, or related field, and is a rigorous and logical thinker. They will use their skills to wrangle clinical data, analyze using machine learning/deep learning and other signal processing techniques, troubleshoot, and present results using clear and organized data visualizations and appropriate biostatistics. Candidates should be fluent in Python, including tools such as Tensorflow, Keras, or PyTorch; Pandas; Scikit; as well as tools for data visualization (e.g. d3.js, R, Matlab, pylab, seaborn, etc). Familiarity with computing in the cloud/on HPC is a plus.

Project Manager, Data Science

APPLY. The successful individual will be excited to work in a research lab at UCSF dedicated to translational research in medical imaging and machine learning. Under supervision, the candidate will be involved in studying how computational approaches to image analysis can improve diagnostic accuracy in medical imaging, which is critically important across medical specialties. Responsibilities including data extraction/labeling, organization, and entry; database management, and data analysis. In close collaboration with the PI, the individual will assist with clinical study design, protocol management and coordination, IRB submission and management, and scientific writing. The successful candidate will be interested in translational research and medicine (ideally, cardiovascular); and will also have a working knowledge of Python, the command line, Excel, and Mac and/or Windows operating systems. Candidates will have dual Bachelor's degrees (or major and minor) in a biology- or pre-med field as well as a computer science, engineering, or math-related field, and will have excellent organization, multi-tasking, teamwork, and communication skills.

Working in the Arnaout Lab

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 the Bakar Institute, Center for Intelligent Imaging, Biomedical Informatics graduate program, 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. Positions offer an opportunity to participate in cutting-edge, multi-disciplinary 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. Positions also provide 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. Email rima(dot)arnaout(at)ucsf(dot)edu with your CV and a clear but brief letter of interest, or click on the position to apply directly at UCSF BrassRing.