Post Doctoral.Associate - 26005937

Post Doctoral.Associate Med-Biomedical Informatics - Pennsylvania-Pittsburgh - ( 26005937 ) We are seeking a highly motivated and productive postdoctoral researcher to contribute to federally funded projects in machine learning, regulatory genomics, single-cell multi-omics, spatial transcriptomics, and precision oncology. The successful candidate will apply and develop computational methods, take ownership of research projects, and advance them toward reproducible software, scientific deliverables, and peer-reviewed publications. Key Responsibilities • Lead computational projects from study design and data processing through modeling, validation, biological interpretation, and publication. • Analyze large-scale bulk, single-cell, multi-omic, and spatial datasets. • Develop and evaluate machine-learning methods for classification, prediction, multimodal integration, and regulatory inference. • Apply rigorous validation practices, including appropriate data partitioning, cross-validation, baseline comparisons, external validation, and assessment of bias and generalizability. • Develop reproducible, well-documented, version-controlled, and open-source software. • Prepare publication-quality figures, manuscripts, presentations, and grant reports. • Collaborate effectively with computational, experimental, and clinical investigators. • Provide regular, structured progress updates and communicate challenges, absences, or anticipated delays promptly. • Meet agreed-upon milestones and deadlines, respond constructively to feedback, and complete revisions and action items. • Support the mentorship of junior researchers, as appropriate. Required Qualifications • PhD in computational biology, bioinformatics, biostatistics, statistics, mathematics, computer science, or a related quantitative field. • Strong programming skills in Python and/or R. • Demonstrated expertise in machine learning, statistics, omics data analysis, or computational biology. • Understanding of model selection, regularization, overfitting, data leakage, class imbalance, performance evaluation, and generalization. • Ability to translate broad research objectives into specific analyses, timelines, and deliverables with limited supervision. • Demonstrated ability to independently plan, implement, troubleshoot, and complete computational research projects. • Evidence of completing projects through peer-reviewed View the full job description on the employer's website. Equal employment opportunity, including veterans and individuals with disabilities. PI287268465 / 11-9121.01 Clinical Research Coordinators