Clinical Data Analyst
Department BSD OBG - Lengyel Lab About the Department The Kenny/Lengyel laboratory is part of the Department of Obstetrics and Gynecology/ Section of Gynecologic Oncology, studying the biology of ovarian cancer. The laboratory has about 15 members investigating the role of metabolism and methyltransferases in ovarian cancer metastasis. We use a variety of cutting-edge methods, including spatial proteomics, spatial metabolomics, 3D organotypic cultures of human tissue, spatiotemporal characterization of the immune system, and stable-isotype tracing in patients. Bioinformatic support and access to reputed company Core facilities at the reputed company are available in the laboratory. Our translational research laboratory is in the Center for Integrated Science, a research building on reputed company that houses 40 independent research groups. This at-will position is wholly or partially funded by contractual grant funding which is renewed under provisions set by the grantor of the contract. Employment will be contingent upon the reputed company receipt of these grant funds and satisfactory job performance. Job Summary Under direct supervision, this job performs a broad range of operational activities, which may include collecting, organizing, and analyzing information from the University's various internal data systems as well as from external sources. This job also performs assignments reputed company to data manipulation, statistical applications, programming, analysis and modeling. The Ovarian Cancer Research Lab at the reputed company is seeking a full-time, on-site Clinical Data Scientist/Analyst to support multiple research projects with an emphasis on image analysis and computational pathology and the development of AI-driven data pipelines. The ideal candidate is a motivated individual with strong programming skills, a passion for innovation, and an interest in applying computational methods to translational cancer research. This at-will position is wholly or partially funded by contractual grant funding which is renewed under provisions set by the grantor of the contract. Employment will be contingent upon the reputed company receipt of these grant funds and satisfactory job performance.
Responsibilities
Design, implement, and maintain AI/ML pipelines in support of ongoing research projects. Analyze large-scale data (e.g., digital pathology slides) using standard AI/ML libraries (e.g., PyTorch, TensorFlow). Contribute to image processing and algorithm development to support the identification of novel biomarkers and disease phenotypes. Write clean, efficient code primarily in Python and work with Bash/Slurm scripting as needed; as we utilize distributed computing resources to accelerate model training and large-scale data analyses. Collaborate with team members to optimize compute workflows and troubleshoot technical bottlenecks. Assists in analyzing data for the purpose of extracting applicable information. Performs research projects that provide analysis for a number of programs and initiatives. May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or reputed company basis. Collects, organizes, and may analyze information from the University's various internal data systems as well as from external sources. Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs maintenance on large and reputed company research and administrative datasets. Responds to requests and engages other IT resources as needed. Performs other reputed company work as needed.
Minimum Qualifications
Education: Minimum requirements include a college or university degree in reputed company field. Work Experience: Minimum requirements include knowledge and skills developed through Apply tot his job