-
Learning: Apply shape-correspondence and machine-learning approaches, including spectral/graph-based surface alignment and autoencoder-based shape extraction, to compare limb and joint morphology across
-
Associate will perform research using advanced behavioral, chemogenetic and neuroscience approaches in rodent memory, stress and reward self-administration models. Research will use orexin-cre rats and local
-
well as machine learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the
-
aligned with the aims of the Addiction & Decision Neuroscience Lab (ADN). Current work focuses on cognitive modeling of decision-making in both laboratory tasks and real-world settings, as well as machine
-
: Strong skills in developing biosignal processing algorithms and implementing machine learning models for data interpretation. Technical Oversight: Ability to monitor complex data collection processes and
-
cluster and apply this pipeline for novel machine learning model. Essential duties and responsibilities include the following: Build and test analysis pipelines for Next Generation Sequencing data
-
to effectively learn this technique will be needed. Effective oral and written communication skills. Must be computer literate with proficiency and working knowledge of database and reporting tools such as
-
Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
-
of these metabolites. In addition, the candidate may explore the biological functions of these metabolites using preclinical models and clinical cohort data. The successful candidate also will mentor and supervise
-
learn, work, and serve the public at Rutgers locations across New Jersey and around the world. Posting Summary Rutgers, The State University of New Jersey has opening for two (2) Postdoctoral Associates