Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- UNIVERSITY OF HELSINKI
- Imperial College London
- University of Utah
- Wayne State University
- ;
- ; University of Cambridge
- CNRS
- Duke University
- Escola Superior de Saúde do Politécnico do Porto
- Institute for bioengineering of Catalonia, IBEC
- Leibniz
- Nature Careers
- SINTEF
- SciLifeLab
- University of Bergen
- University of California Irvine
- University of Cambridge
- University of Florida
- University of Glasgow
- University of Luxembourg
- University of Malta
- University of Newcastle
- University of Pennsylvania
- University of Pittsburgh
- University of Sheffield;
- University of Strathclyde;
- University of Tübingen
- Uppsala universitet
- 18 more »
- « less
-
Field
-
is to discovering the mechanisms of resistance evolution and develop biomarkers that can predict which patients are at risk of developing resistance. Work at Manchester and Liverpool has focused
-
expertise in force field development, weighted ensemble rare-event sampling, and scientific software development. The researcher will be the lead developer of the WESTPA software for weighted ensemble
-
relevant bioinformatics software packages). Develop models to identify transmission routes and predict AMR. Analyse data, interpret results and compile findings into detailed reports for regular project team
-
into quantitative frameworks for prediction of the contribution of An. stephensi to malaria transmission, and optimising surveillance and control for this and other native vector species in urban settings. 2. Build
-
, … available in the BIOMOD2 suite (https://biomodhub.github.io/biomod2/ ) and if these SDM can predict not only species presence distribution but maximum species population density. Second objective is to gather
-
/SinglePageApplicationForm.aspx… Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications Professional skills Experience in: Reinforcement Learning (RL), Model Predictive Control (MPC
-
using language identification, such as text corpora for rare languages. Language identification methods ground their predictions on training corpora for a finite number of separate languages. In practice
-
bioinformatics pipelines for the metabolomics data analysis and visualization of metabolomics data, support the integration of software tools for data (pre-)processing, biomarker discovery, and predictive
-
and visualization of metabolomics data, support the integration of software tools for data (pre-)processing, biomarker discovery, and predictive modelling. Furthermore, serve as the metabolomics subject
-
Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic