Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- The University of Auckland
- FEUP
- NOVA.id.FCT- Associação para a Inovação de Desenvolvimento da FCT
- Universidade de Coimbra
- University of Southern Queensland
- CSIRO
- Duke University
- Faculdade de Medicina Veterinária
- INESC MN
- Indiana State University
- Indiana University
- Instituto Politécnico de Setúbal
- National Research Council Canada
- Nuclear Science and Engineering Undergraduate Scholarship - Department of Defence
- Queensland University of Technology
- University of Alaska
- University of Manchester
- 7 more »
- « less
-
Field
-
specifically in Business Analytics & Decision Sciences, and candidates must be able to teach in one or more of the following: core analytics (machine learning, statistics, optimisation, decision analysis
-
Aid and Scholarships, Office of the Registrar, Office for Veterans and Military personnel, as well as other areas supporting student enrollment. The Division also oversees and provides insight for its
-
13 (5 points); Bachelor Degree classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks
-
classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks, Hierarchical Decision and Control Systems with main
-
Artificial Intelligence, with an emphasis on the development of methodologies and techniques for Evolutionary Computation and Machine Learning, with an emphasis on task allocation and route planning methods
-
clinical data and machine learning algorithms. The main activities include: Data Processing: • Collection of historical patient data (demographics, clinical history, outcomes of interventions). Data cleaning
-
clinical data and machine learning algorithms. The main activities include: Support for AI Model Development: • Collaborating on the training of predictive models under the supervision of the scientific team
-
, and visualization, time series processing, and machine learning. Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. 3. Financial component - According
-
. They should be able to thrive in the multidisciplinary culture of INESC MN and fit in projects involving physics, microfabrication, machine learning, mechatronics, etc. and be able to communicate
-
fellowship will be involved in the execution of the following tasks: 1 - Train the metamodels using machine learning techniques; 2 - Validate the machine learning results with experimental results. The aim