| Test Automation | Created Date | Created By | Next Notification Date | Last Notification Date | Request ID | Type | Type_ID | Request Status | Requester Name | Requester Email | Requester Email Copy | Skills | Current Department | Knowledge | Department | Program | Description of Request | Skills/Experience | Effort Required | Available Start Date | Start Date | Availability | End Date | Funded | Flexible Dates | Hybrid Option | Request_ID_2 | Additional Information | CONNECT | Modified | Modified By | Update Alert | ||||
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| 1 |  | 12/15/25 5:16 PM | web-form@smartsheet.com | 12/26/25 | TC0162 | Research Project | 2 | Open | Zoe Quandt | Zoe.Quandt@ucsf.edu | Zoe.Quandt@ucsf.edu | HPC/GPU Computing Python R | Machine Learning non-ML Statistics | My lab focuses on endocrine side effects of cancer immunotherapy using a multimodal approach. I am looking for people with experience with programming in R and/or python to support analysis looking for novel autoantibodies and genetic risk. | Experience with use of statistical programs such as R and python are required. Statistic experience is a plus. | 25% | Yes | People who can dedicate 25% effort or more for at least a semester would be wonderul. | https://app.smartsheet.com/b/form/0196d62f5a067732922e38b82707d53b?Request%20ID=TC0162&Type_ID_2=2 | 12/15/25 5:16 PM | automation@smartsheet.com | | ||||||||||||||
| 2 | | 12/15/25 7:31 PM | web-form@smartsheet.com | 12/26/25 | TC0163 | Research Project | 2 | Open | Minnie Sarwal | minnie.sarwal@gmail.com | minnie.sarwal@gmail.com | Git/GitHub JQuery/JavaScript MLib/Machine Learning Python R | Machine Learning | Omic analysis of kidney transplant samples already conducted in the lab and to utilize this and public data coupled with spatial imaging data analysis to better understand the pathobiology of immune injury and rejection and to utilize this information to conduct drug repurposing studies to identify new drugs for treatment of CMV disease and graft rejection | Archival data and sample sets in lab and deep expertise in lab and with PIs to support immunology based and statistical analysis of kidney transplant rejection with Pi’s in transplant and computational biology | 01/30/26 | 01/30/26 | 50% | 01/30/27 | Yes | Would lead to publication and funding application | https://app.smartsheet.com/b/form/0196d62f5a067732922e38b82707d53b?Request%20ID=TC0163&Type_ID_2=2 | 12/15/25 7:31 PM | automation@smartsheet.com | | |||||||||||
| 3 | | 12/20/25 12:47 PM | web-form@smartsheet.com | 12/30/25 | TC0164 | Research Project | 2 | Open | Edilberto A.orim | amorim@ucsf.edu | amorim@ucsf.edu | Apache Spark Git/GitHub HPC/GPU Computing MLib/Machine Learning NLP Tools PyTorch Python R SQL TensorFlow | Machine Learning non-ML Statistics | Our group focuses on large scale deep phenotyping of patients with acute brain injury. This includes quantitative and machine learning work using continuous invasive and non-invasive EEG, brain MRI, and high-resolution electronic health record data. | Familiarity programming (python, MATLAB, or R depending on interests) | 01/02/26 | 90% | 12/31/26 | Yes | Visit our website: https://alab.ucsf.edu/ | https://app.smartsheet.com/b/form/0196d62f5a067732922e38b82707d53b?Request%20ID=TC0164&Type_ID_2=2 | 12/20/25 12:47 PM | automation@smartsheet.com | | ||||||||||||
| 4 | | 01/12/26 5:26 PM | web-form@smartsheet.com | 01/23/26 | TC0165 | Research Project | 2 | Open | Sharat Israni | sharat.israni@ucsf.edu | sharat.israni@ucsf.edu | Git/GitHub Python SQL | Biology non-ML Statistics | Based on student interests, we can offer opportunities for a variety of projects that help advance UCSF's Knowledge Computing platform. Students will work to develop an integrated biomedical summarizer, i.e. an interface to connect and summarize information about a biomedical entity from multiple knowledgebases. Some services (e.g. Bioportal) create these connections via ontologies, but results are not returned in a programmatic (AI-ready) way or in a user-friendly, summary form. Our team has worked to develop a comprehensive knowledge network and other tools that accomplish pieces of this, but would like to put it all together into a pipeline that serves a specified use-case (which can be suggested by the project team or specified by our faculty). | Undergraduate level knowledge of computer programming & databases is required, along with an interest in and basic understanding of biomedical concepts. Students will learn how to model patient data from electronic health record systems and other related biomedical data repositories; and how to use machine learning tools for prediction, design, and/or development of models. Students will develop their practical programming skills (Python, SQL, and other tools) and gain familiarity with connecting multimodal data types utilizing standard biomedical ontologies. | 10% | Yes | https://app.smartsheet.com/b/form/0196d62f5a067732922e38b82707d53b?Request%20ID=TC0165&Type_ID_2=2 | 01/12/26 5:27 PM | automation@smartsheet.com | | |||||||||||||||
| 5 | | 01/16/26 1:35 PM | web-form@smartsheet.com | 01/26/26 | TC0166 | Research Project | 2 | Open | Elise Harb OD PhD | elise.harb@ucsf.edu | elise.harb@ucsf.edu | Git/GitHub Python R | non-ML Statistics | Our work investigates the role of the visual environment (habitual indoor and outdoor activities, e.g. device use, nearness of objects, lighting characteristics) of a child and how it relates to the development and/or progression of myopia (nearsightedness). Myopia is rapidly becoming more prevalent and has tremendous economic, social and disease burden. This project has a tremendous amount of visual environment data from wearable technologies worn by kids which needs dynamic analysis | - Proficient coder (Python, R, Matlab) - Interest in doing translational research | 35% | Yes | https://app.smartsheet.com/b/form/0196d62f5a067732922e38b82707d53b?Request%20ID=TC0166&Type_ID_2=2 | 01/16/26 1:35 PM | automation@smartsheet.com | | |||||||||||||||
| 6 | | 01/31/26 12:38 PM | web-form@smartsheet.com | 02/10/26 | TC0167 | Research Project | 2 | Open | Everlyn Kamau | everlyn.kamau@ucsf.edu | everlyn.kamau@ucsf.edu | Git/GitHub Python R | non-ML Statistics | Developing a simple and open-source digital tool for reproducible reporting and data interpretation. This project will write analytical workflows and consolidate them plus any associated data into an application or a digital tool to be hosted online and shared freely as a file. Our work has been the basis of new WHO guidelines for use of serology to inform trachoma elimination endgame. This project contributes to continued efforts towards trachoma control and elimination, with potential for wide-reaching impact in NTDs. Epidemiology, global health, disease surveillance | - Coding in R, Python, including writing markdown and jupiter notebooks - Unix/Linux command line - Shiny frameworks - Git / GitHub | 06/01/26 | 100% | Yes | Laptop / computer will NOT be provided. Self-drive and highly motivation with an interest in contributing to global health research and infectious diseases. Location of project - UCSF Mission Bay campus | https://app.smartsheet.com/b/form/0196d62f5a067732922e38b82707d53b?Request%20ID=TC0167&Type_ID_2=2 | 01/31/26 12:38 PM | automation@smartsheet.com | | |||||||||||||