Sort by
Refine Your Search
-
acquire additional skills and be involved in the analysis of single-cell RNA Sequencing, WES, and in situ transcriptomics data. Trainees will present their findings at regular lab meetings, departmental
-
, messy, heterogeneous healthcare data. * A team player who thrives as a member of a highly functional cross-disciplinary team Preferred Elements * Prior experience with AI in healthcare settings. * Prior
-
scientific writing skills Preferred qualifications: Hands-on experience with single-cell and spatial transcriptomic analysis Familiarity with multi-omic data integration workflows Cancer biology background
-
: examples include work on food analysis, product formulation, microbial food, and culinary sciences. Bioreactor design, bioprocess engineering, downstream processing applied to future food. Artificial
-
healthcare data. * A team player who thrives as a member of a highly functional cross-disciplinary team Preferred Elements * B.S, M.S., and/or PhD in Computer Science, Biomedical Informatics, Machine Learning
-
eligible for basic clinical medical physics training and a tuition fee waiver to enroll in a certificate program with CAMPEP-accredited courses, which covers medical physics didactic elements for people who
-
learning, or a related field Strong background in deep learning and statistical analysis Proficiency in Python, R, and deep learning frameworks (e.g. PyTorch, TensorFlow) Strong written and verbal
-
, biostatisticians, pathologists, data scientists, molecular biologists, and clinical researchers, all of whom contribute their unique expertise to our lab’s work. We employ a broad variety of analysis approaches and
-
interdisciplinary teams, the design and execution of research studies and data analysis, with an overall goal to further the mission of St. Jude to advance research and cures for pediatric catastrophic diseases. St
-
data, bias analysis and minimization, performance metrics and uncertainty quantification, evaluation of continuously learning algorithms, and post-market monitoring. Learning Objectives: Under