Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
, Bayesian optimization, or reinforcement learning. Experience with high-performance computing (HPC). Experience supervising students or junior researchers. What you will do As a postdoctoral researcher, you
-
. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with
-
Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field observations—including
-
project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD fellow will be part of a growing
-
medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data-driven. Will
-
is home to a consortium of postdoctoral fellows who provide modeling expertise for a wide range of projects as integral members of those research teams. Unit URL https://imci.uidaho.edu/ www.uidaho.edu
-
based on citizenship or visa status. Preferences Preferred • Experience using or modifying machine learning models such as decision trees, Bayesian models, deep learning architectures, transformers
-
page to watch video, or click here to open video) About the position The position is part of the research project “Prediction of genetic values and adaptive potential in the wild (GPWILD)” (https
-
should apply online at https://utah.peopleadmin.com/postings/204175 . Required materials: Letter of interest (cover letter) CV Research statement Teaching statement Exemplar publications that highlight
-
Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https