73 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"SUNY" positions at Center for Drug Evaluation and Research (CDER)

FDA Fellowship - Optimization of Drug-induced Liver Injury Analysis Methods

Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 21 hours ago

methodologies, statistical analysis of rare adverse events, and understanding of health disparities in clinical research. Learning Objectives: You will develop skills in safety signal detection, learn to identify

FDA Studying the Critical Quality Attributes of Multispecific Antibodies/Fusion Proteins (SARITA 4400)

Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | about 21 hours ago

trispecific fusion proteins. Using breast and ovarian cancer cell models, you will help develop bioassays to evaluate and improve the quality, safety, and anti-tumor activity of FDA-regulated products. Learning

FDA Quantitative Systems Pharmacology Modeling for Fetal Cardiac Safety Fellowship

Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 20 hours ago

turn this project will advance safety and understanding of potential toxicity of FDA-regulated products in the perinatal population. Learning Objectives: Under the guidance of the mentor, you will gain

FDA Fellowship - Development of AI Technologies for Causality Assessment

Center for Drug Evaluation and Research (CDER) | Jefferson, Arkansas | United States | about 21 hours ago

or risks from sources other than clinical trials. Learning Objectives: You will join generations of scientists in the field of pharmacoepidemiology, pharmacovigilance, and drug safety through this learning

FDA Development of Cell-based Reporter Assays for FSH, LH and hCG

Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | about 21 hours ago

be utilized to test unstressed and stressed FSH, LH and hCG samples, comparing their performance with the current in-use rat potency assays. Learning Objectives: During the appointment, you will have

FDA Biomarker Analysis: Addressing the Gap Between Patient Enrollment Applications and Pharmacodynamic Effect Evaluation

Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 21 hours ago

early. Learning Objectives:  Under the guidance of the mentors, you will have the following learning outcomes; Learn the FDA database navigation system Learn how the biomarker assists the drug development

FDA Utilizing Artificial Intelligence to Enhance Pharmacovigilance and Inspection Fellowship

Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 21 hours ago

mentor, you will engage in cutting-edge research activities to learn how to develop and implement artificial intelligence-enabled systems for surveillance and inspection. Key activities will include

FDA Quality Knowledge Management Throughout the Drug Product Lifecycle

Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 21 hours ago

knowledge base is dispersed and “hidden” in different parts of the Agency. Learning Objectives: Under the guidance of the mentor, the participant will train on pharmaceutical science, laws and regulations

FDA Postdoctoral Fellowship - Clinical Pharmacology and Immunogenicity Data Assessment

Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 20 hours ago

communicated in FDA-approved product labeling, comparing review findings with final labeling language to identify alignment patterns and improvement opportunities. Learning Objectives: Your educational training

FDA Research Fellowship: Biologic Products and the Regulatory Evaluation of Biosimilars

Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 21 hours ago

or limited multivariate analysis. However, the increasing dimensionality and complexity of analytical data demand AI/ML-based frameworks capable of learning nonlinear, high-dimensional relationships between