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NYU Grossman School of Medicine – Post-doctoral associate
Company NameNYU Grossman School of Medicine
Position TitlePost-doctoral associate
Company Information
Academic medical center
Duties and Responsibilities
We are seeking a motivated Post-doctoral Fellow to join our team and contribute to an exciting research program. As part of the recently launched NIH Common Fund Complement-ARIE program, the NYU-Sage New Approach Methodologies (NAMs) Data Hub and Coordinating Center will establish and execute a framework for evaluating and validating novel in vitro, in chemico and in silico methodologies. Working together with researchers across the NAMS Consortium, we will plan for and execute risk and credibility assessments for newly-developed NAMS technologies to comply with FDA and other regulatory agency requirements. The successful candidate is expected to get training in this emerging field and contribute to its general methodologies. Additionally, this position is expected to support and/or lead the assessment of credible, reproducible, and regulatory-ready NAMs models. Responsibilities may include defining the model’s context of use (COU), scope, assumptions, limitations, risk profile, credibility goals, and acceptance criteria; assessing metadata completeness and reproducibility; and supporting verification, validation, uncertainty quantification, sensitivity analysis, robustness testing, and regulatory documentation.
Job Responsibilities:
• Assist in developing and implementing risk and credibility assessment frameworks for NAMs, including computational models, mechanistic experiments/simulations, organoid models, technologies in toxicology, and combinatory NAMs.
• Support context-of-use (COU) definition, applicability analysis
• Support/consult experimental designs of NAMs technology development
• Contribute to verification and validation (V&V) studies, including software testing, computational reproducibility, numerical consistency checks.
• Assist with statistical and computational analyses using experimental, simulation, omics, or clinical data.
• Uncertainty quantification, and robustness/sensitivity evaluations.
• Support development and maintenance of reproducible computational pipelines.
• Assist with preparation of technical and regulatory documentation, including validation reports, SOPs, audit-readiness documentation, and quality-management records.
• Establish pipeline QA/QC
• Support alignment with relevant regulatory agencies (FDA, EPA) and standards frameworks.
Position Qualifications
Minimum Qualifications
• PhD in Biomedical Informatics, Biostatistics, Computational Biology, Toxicology, Systems Biology, Data Science, Applied Mathematics, Computer Science, and a related quantitative field.
• Experience with scientific or statistical programming using R, Python, SAS, MATLAB, or similar programming/computational tools.
• Familiarity with statistical analysis, computational modeling, machine learning, and data analysis workflows.
• Experience working with biological, clinical, toxicology, omics, or other complex scientific datasets.
• Knowledge of reproducible research practice, including documentation, metadata, version control, and workflow organization.
• Strong analytical, problem-solving, and technical communication skills.
• Ability to work independently and collaboratively within multidisciplinary research teams.
• Excellent written and verbal communication
Preferred Qualifications
• Experience with New Approach Methodologies (NAMs), computational toxicology, physiologically based pharmacokinetic (PBPK) modeling, systems biology, or mechanistic modeling.
• Familiarity with risk and credibility assessment frameworks such as ICH M15, ASME V&V 40, FDA computational modeling guidance, GAMP 5, ISO 14971, or related regulatory/scientific standards.
• Experience with verification and validation (V&V), uncertainty quantification, or reproducibility assessment.
• Familiarity with AI/ML model evaluation, predictive modeling, or model-performance assessment.
• Experience with reproducible computational workflows, pipeline development, or data-engineering practices.
• Experience using Git/version control, containerized workflows, cloud computing, or high-performance computing (HPC) environments.
• Experience preparing technical documentation, SOPs, validation reports, or regulatory/scientific reports.
• Exposure to regulated research environments (e, g, NDA filing), quality-management systems, or electronic-record compliance frameworks such as 21 CFR Part 11.
• Experience with SoMD and interactions with regulatory agencies such as FDA and interest in regulatory science.
• Experience in toxicology and translational biomedical research.
Salary RangeCompetitive
Benefits
Standard NYU Langone Post-doc benefits.
Application Instructions
Send email to chang.yu@nyulangone.org