Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- INESC ID
- University of Porto
- FCiências.ID
- ISCTE - Instituto Universitário de Lisboa
- Instituto de Telecomunicações
- Nova School of Business and Economics
- Politécnico de Leiria
- Universidade de Coimbra
- Aveiro University
- CMU Portugal Program - FCT
- COFAC
- FCT NOVA - UNIDEMI
- Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra
- Instituto Superior de Economia e Gestão
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S)
- NOVA Institute for Medical Systems Biology
- Nature Careers
- RAEGE-Az
- Seed Robotics
- UNINOVA - Instituto de Desenvolvimento de Novas Tecnologias
- Universidade Nova de Lisboa
- Universidade do Minho - ISISE
- 13 more »
- « less
-
Field
-
6. of this Notice. Preferred factors: Knowledge in machine learning and programming (Python), deep learning (e.g., tensorflow, pytorch) and time-series modeling in marine ecology applications
-
with e-CALLISTO instruments or Software-Defined Radios (SDRs). · Familiarity with machine learning for astrophysical data analysis. · Knowledge of solar radio data pipelines and event classification
-
Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | 11 days ago
: Electrotechnical and Computer Engineering. Admission requirements: Students enrolled in a PhD. program in Electrotechnical and Computer Engineering, or in related areas, or alternatively, an MSc degree in
-
8 Oct 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Biomedical engineering Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
-
Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 6 days ago
with Machine learning approaches, to refine the ataxin-3 network. The most affected PPIs, will be validated using commercial fibroblasts from MJD patients, and standard molecular tools such as Western blotting
-
spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication
-
of establishing relationships between signal sources and predicting commands; 6. Design of machine learning and adaptive models that ensure the continuous evolution of the system, increasing the autonomy and
-
, stringent layout design rules demand new design automation solutions beyond the actual state-of-the-art. The proposed work plan focuses on the thorough exploration of innovative generative machine learning
-
vision systems, on the consideration of strong constraints on processing times and on the use of machine learning techniques in specific contexts (e.g. embedded targets, little data or explainable AI
-
developing statistical and machine learning approaches for the integration of cancer multi-omics data and the analysis of CRISPR-based screens. Responsibilities include designing bioinformatics workflows