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Ficha de projeto

Nome

Assistant Professor in Engineering and Management of Systems

Valor total do projeto

123,39 mil €

Valor pago

0 €

Financiamento não reembolsável

123,39 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.P2023.14864.TENURE.034

Sumário

Job description.   There are seven main tasks the Assistant Professor must accomplish:a. Promote and develop the research-teaching components.  In terms of research, it is expected the Assistant professor will integrate CEGIST and foster and develop her/his research within the MOSAIC (systems modelling and Methods of Operations research And analytICs) group, namely to develop internal and external (national and international) collaborations and bring funding through the application to national and international competitive calls for research projects.  In the teaching component it is crucial to develop the group of disciplines in Operations Research and Analytics (ORA). In this teaching component, it is also important the Assistant Professor will design new courses to promote the integration of ORA and Intelligence Artificial (AI) mainly ML tools, will develop new teaching methods with the help of AI techniques, and will supervise Master and PhD students in cutting-edge research in the frontiers of ORA and AIb. Apply ORA and AI (ML) techniques in business and other real-world problems . It is expected to develop ORA/ML tools and establish a network community and collaborate with other business schools and industry partners to apply ORA and IA techniques.c. Curriculum Development . Related with task a) develop courses that make the bridge between ORA, AI (ML), and Business Analytics (BA).d. Foster industry Interaction . To take advantage of, as for example, Tecnico+, to organize specialized short courses.e. Publishing and Dissemination .  To publish and disseminate his activity in top peer reviewed journals in the frontier of ORA and AI (ML).f. Commitment with ethical practices .  The Assistant professor should be a continuous commitment to promote fairness, transparency, and accountability in her/his daily teaching, research, and consulting activities. Scientific profile . There are four fundamental aspects to define the required profile:a. Educational background . PhD in Operations Research, Industrial Engineering, Business Analytics, or related field with a focus on Machine Learning in particular, or Artificial Intelligence in general.b. Informatics background .  Strong skills in programming languages (in particular, Python, Julia, and C++), machine learning tools (e.g., Scikit learn), multipurpose data analytics or programming platforms (e.g., MATLAB, Mathematica), optimization solvers (in particular, Cplex, Gurobi, GLPK), visualization tools (e.g., Matplotlib), and simulation tools (e.g., AnyLogic ans Simio).c. Research experience . Record on innovative research in ORA with Expertise in Machine Learning (impact publication with a focus on the main field of Operations Research while showing expertise in Machine Learning).d. Teaching experience .  Demonstrate she/he can teach undergraduate and graduate courses in ORA and Business Analytics (with focus on Machine Learning) and include in the courses industry case studies.e. Additional requirements : Demonstrate the capabilities to mentorship and research collaboration, to bring funding, to communicate and disseminate her/his findings and successful business applications, to make industry collaboration and partnerships, demonstrate commitment to continuous professional development in the context of ORA and IA (especially machine Learning), to make contributions to the academic community. Rationale . There are three main reasons for hiring a new faculty member with the required profile established in the previous point.a. Department strategic vision . The department´s strategic vision, set out in its self-evaluation report, aims to divide the EMS area into two pedagogical areas and create three groups of disciplines, of which ORA is one of them.  Furthermore, the new challenges of ML and its close relationship with ORA have led to the emergence of a need that leads to the hiring of an Assistant Professor with the profile previously established.b. Deficit in the teaching-research components in the group of UCs in ORA . Currently there are the equivalent to 2.5 teachers in this group, given the current number of UCs, the near future needs, the sabbatical leavings, and the mid-term teaching projects, as mentioned in Point 1.a.), it is obvious that this group has a pressing need to hire.c. Academic and research excellence by promoting faculty diversity .  As a consequence of the strategic vision of the department and research unit it is important to promote the diversity of faculty members and the intellectual enrichment by hiring Assistant Professors with competences in ML/AI, which are important to respond to emerging trends.

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

Na realização dos Avisos de Candidaturas são solicitadas candidaturas para a escolha dos projetos e dos beneficiários finais a quem é atribuído o financiamento.

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

9,3
Nota importante

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

Critérios de seleção

Os critérios de seleção de financiamento a que este projeto e respetivo beneficiário final esteve sujeito e a sua classificação podem ser consultados em detalhe na plataforma Recuperar Portugal.

Beneficiários

Beneficiários intermediários

Beneficiários

Contratação pública

Os Beneficiários que sejam entidades públicas operacionalizam o seu projeto através da celebração de um ou mais contratos de fornecimento de bens ou serviços com entidades fornecedoras, através de procedimentos de contratação pública.

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

123,39 mil €

Valor total do projeto

Onde foi aplicado o dinheiro

Por concelho

1 concelho financiado .

  • Lisboa 123,39 mil € ,
Fonte EMRP
09.03.2026
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