Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
Multiscale Modeling, Process Control, Hybrid Modeling and Machine Learning. Create a Job Match for Similar Jobs Logo About The Ohio State University Join Ohio State’s community.Together, we’ll create
-
Engineering, Chemistry or Mathematics preferred. Candidate must have 3 years of relevant research experience. Required Experience: Demonstrated experience in multiscale modeling and/or process modeling and
-
disease to join our CDC-funded project team to strengthen partnerships with public health in the Ohio River Valley and develop predictive models and hazard maps that inform public health decision-making
-
, machine learning techniques, and domainspecific scientific knowledge. This role is responsible for processing and analyzing complex datasets, developing and optimizing machine learning models, and
-
to understanding the biology of coronaviruses, paramyxoviruses, and pneumoviruses, understanding vaccine candidates and therapeutics for infectious diseases. It will also involve developing animal models
-
background in zoonotic and vector-borne disease to join our CDC-funded project team to strengthen partnerships with public health in the Ohio River Valley and develop predictive models and hazard maps that
-
data products. The Senior Data Engineer leads the end-to-end development lifecycle - data ingestion, transformation, modeling, testing, deployment, and monitoring - while championing modern engineering
-
Erie Basin. The Senior Research Scientist will be responsible for defining and leading innovative research directions, developing novel modeling and analytical frameworks, and integrating field
-
(e.g., cryoSPARC, RELION, Phenix, Coot). Expertise in computational modeling and structure-based protein engineering. Strong interest in AI-based protein design approaches. Prior research experience in
-
learning models, and integrating physics-based insights to enhance model performance and interpretability. The incumbent ensures the accuracy, reliability, and integrity of analytical outputs through