138 non-coding "Data driven Materials Modeling" Postdoctoral positions at Rutgers University
Sort by
Refine Your Search
-
, Mechanical Engineering, Civil Engineering, Physics, or a related field is required. Knowledge of the mechanical behavior of materials and some form of materials modeling (e.g., density functional theory
-
Science Foundation, and others that include a mix of research design, fieldwork, data science, simulation modeling, writing, and presentations. The overarching goal of the Postdoctoral Associate will
-
Associate is to conduct research on characterizing non-coding regulatory elements in humans and understanding how these elements change across different conditions. The project will involve developing
-
Position Details Position Information Recruitment/Posting Title PostDoctoral Associate in Artificial Intelligence/Machine Learning and Data Science Department Quantitative Biomedicine Inst Salary
-
, applied mathematics, or a closely related field by the start date of the appointment. · Experience in numerical modeling related to one or more of the following areas: computational astrophysics
-
-management skills. Oral and written communication skills, including the ability to communicate research findings to both academic and non-academic audiences. Proficiency with standard office and data
-
, and agricultural impacts, among others. Successful candidates will be involved with observational data analysis, numerical modeling of natural hazards, and outreach to local stakeholders. Candidates
-
(DL), and big data analytics. His lab is developing new modeling strategies that can integrate heterogeneous public data into model development. Another major research interest is the use of large
-
(DL), and big data analytics. His lab is developing new modeling strategies that can integrate heterogeneous public data into model development. Another major research interest is the use of large
-
(DL), and big data analytics. His lab is developing new modeling strategies that can integrate heterogeneous public data into model development. Another major research interest is the use of large