Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- FCiências.ID
- Instituto Pedro Nunes
- Universidade de Coimbra
- Faculdade de Ciências e Tecnologia
- Nova School of Business and Economics
- University of Minho
- INESC ID
- Instituto Superior de Economia e Gestão
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- International Iberian Nanotechnology Laboratory (INL)
- Politécnico de Leiria
- RAEGE-Az
- Universidade Nova de Lisboa
- Universidade de Aveiro
- University of Trás-os-Montes and Alto Douro
- Value for Health CoLAB
- 6 more »
- « less
-
Field
-
domains. The successful candidate will: Develop algorithms to model team performance based on interpersonal (e.g., monitoring, communication) and cognitive (e.g., shared mental models) processes. Design an
-
requirement Work plan: The candidate will carry out R&D activities within the scope of the 2022.06672.PTDC project, namely: 1) Review of the literature on adaptive mesh generation algorithms for singular
-
Reconstruction from clinical arthroscopy video. The research will focus on investigating and advancing multi-view feed-forward algorithms to tackle the specific challenges of the arthroscopic environment, where
-
algorithms for classifying modes of locomotion and assessing fall risk; iv) integration and control of balance recovery through slip detection tools in a commercial exoskeleton, using ROS2, DMPs, CPGs, and
-
of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
-
Researcher, of the FCiências.ID Scientific Research Career, within the scope of the project HOFGA: The Hardness of Finding Good Algorithms (Ref. HORIZON-ERC-STG-101041696), financed by the European Union´s
-
quantum advantage; Classical simulation algorithms for noisy quantum devices; Boson sampling and related quantum computational advantage proposals; Mandatory Qualifications Education PhD degree in Physics
-
intelligence algorithms.”, financed by National public entities (IFAP IP), under the following conditions: Scientific Area: Geospatial Engineering Admission requirements: Candidates must meet the following
-
requirements, as well as the design of data models, synchronisation algorithms and analysis and learning models applied to brain and physiological signals. The objectives of this fellowship are: 1. To survey
-
; Develop algorithms that adjust the type of pedagogical scaffolding. The goal is always to guide the student without giving the answer, but the way of guiding will be the focus of the adaptation. Fine-tuning