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Ficha de projeto

Nome

INESC TEC Chair in Uncertainty-aware Visual Artificial Intelligence

Valor total do projeto

246,79 mil €

Valor pago

0 €

Financiamento não reembolsável

246,79 mil €

Financiamento por empréstimos

0 €

Data de início

01.02.2025

Data de conclusão

31.03.2026

Dimensão

Resiliência

Componente

Qualificações e competências

Investimento

Ciência Mais Capacitação

Código de operação

02/C06-i06/2024.P2023.14760.TENURE.001

Sumário

???? Job description : We are looking for a Research Assistant of Visual Artificial Intelligence ( VAI ) with a focus on Uncertainty to join our new interdisciplinary research group on VAI . You will develop novel methods and techniques for artificial intelligence in the presence of uncertainty that can help to make more robust decisions supported in complex and high-dimensional visual data in a variety of tasks: 2D/3D image classification, semantic segmentation of 2D images and 3D point clouds, object detection and tracking, biomarker selection, and more.For all these problems, uncertainty estimation of the predictions generated by VAI is crucial. Uncertainty Estimation expresses the degree of uncertainty or lack of precision associated with predictions and can have two major sources: A) Model Uncertainty or Epistemic Uncertainty arises from the model itself due to a lack of evidence (data) or understanding of the model during training or prediction; B) Data Uncertainty or Aleatoric Uncertainty arises from data’s inherent random properties, so it is irreducible by more training data.Other VAI challenges that are of particular importance for visual data are explainability , domain adaptation, transfer learning, data augmentation and few shot learning. You will collaborate with colleagues from the applications that generate data, such as life sciences, biometrics and autonomous driving , and with experts in our group who have a deep understanding of the data. The Interdisciplinary Research Group on VAI Technology is a new research group between INESC TEC and FEUP´s Department of Electrical and Computer Engineering. The group is the result of the great importance INESC TEC places on fostering research between the institutions. Together with the members of the group, you will work at the interface between engineering and AI. An important role for you will be to connect the Visual AI Technology group to new developments in the AI community through your network of collaborators. As an Assistant Researcher at INESC TEC:- you are expected to actively participate in research in the field of uncertainty-aware VAI (uVAI), preferably with a focus on medical applications and autonomous driving;- you are expected to engage in supervising and mentoring in the field of uVAI, VAI and AI;- you are encouraged to develop uVAI methods with your team, measure and adapt VAI methods to data from medical applications and autonomous driving;- to raise funds for the development of new lines of research;- supervise BSc/MSc students and PhD students;The focus of activity is on research that makes a significant contribution to the UN Sustainable Development Goals . Duties will also include publishing research results in reputable international journals and conference proceedings in the field, preparing patent applications and working with IP representatives to finalize patent texts, assisting in the management of approved projects, including the preparation of project proposals and the organization of conferences and scientific events. The role involves working with academic and industrial partners at national and international level. A key requirement is well-documented experience as evidenced by high quality publications. Scientific Profile: The ideal candidate is expected to possess a Ph.D. in Electrical and Computer Engineering or a related field, with a specialization in computer vision and artificial intelligence , and a strong background in statistics . Candidates should possess strong track record for publication and be ready to lead their own research groups independently. They are expected to plan and conduct research and develop extramurally funded research programs involving students. Candidates are also expected to publish peer-reviewed journal articles in high impact journals in visual artificial intelligence or closely related fields. Candidates are also expected to contribute to the growth of the research group, including but not limited to student recruitment/advisement, senior project supervision, internship opportunities, research experiences for undergraduates, etc. Rationale : The position focuses on a specialist in Visual Artificial Intelligence , aligning with the growing relevance of computer vision in various domains. INESCTEC and FEUP have already accumulated a strong training and scientific capacity in the computer vision field, dispersed however over multiple organizations and programmes, without forming a coherent organism. Additionally, the north of Portugal is the home of multiple companies in the field, providing a strong opportunity to establish the path from basic research to technology transfer and societal impact. The new interdisciplinary research group on VAI aims to promote the orchestration of computer vision and pattern recognition skills within INESC TEC and FEUP, with a special focus on research and the structured training of highly skilled ungraduated students and early-stage researchers.

Beneficiários

No âmbito do Plano de Recuperação e Resiliência, existem duas tipologias de beneficiário que têm a responsabilidade de executar os projetos, aplicando o financiamento recebido. Dado o seu papel comum, a referência a estas duas tipologias de beneficiário foi simplificada e unificada no termo “Beneficiário”.
As duas tipologias são:
  • Beneficiários Diretos são aqueles cujos financiamento e projetos a executar constam do Plano de Recuperação e Resiliência negociado e aprovado pela União Europeia;
  • Beneficiários Finais são aqueles cujos financiamento e projetos a executar são aprovados após um processo de seleção, feito através de Avisos de Candidaturas.

Aviso de Candidaturas

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A avaliação do projeto é realizada com base na sua conformidade com os critérios de seleção definidos nos avisos de candidatura, podendo ser atribuída uma nota final, quando aplicável.

Nota final da avaliação

9,6
Nota importante

Poderá encontrar os componentes do cálculo da nota de avaliação no documento de critérios de seleção referenciado em baixo.

Critérios de seleção

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Beneficiários intermediários

Beneficiários

Contratação pública

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De forma a garantir e disponibilizar o máximo de transparência na contratação pública, é aqui disponibilizada a listagem dos contratos que foram celebrados ao abrigo deste projeto e respetivo detalhe que poderá consultar na plataforma Base.Gov. De realçar que de acordo com a legislação em vigor no momento da celebração do contrato, existem exceções que não exigem a sua publicação nesta plataforma, pelo que nesses casos, poderá não existir informação disponível.

Distribuição geográfica

246,79 mil €

Valor total do projeto

Onde foi aplicado o dinheiro

Por concelho

1 concelho financiado .

  • Porto 246,79 mil € ,
Fonte EMRP
10.02.2026
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