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Project sheet

Name

Assistant Professor in Engineering and Management of Systems

Total project amount

123,39 thousand €

Amount paid

0 €

Non-refundable funding

123,39 thousand €

Loan funding

0 €

Start date

01.02.2025

Expected end date

31.03.2026

Dimension

Resilience

Component

Qualifications and Skills

Investment

Science Plus Training

Operation code

02/C06-i06/2024.P2023.14864.TENURE.034

Summary

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.

Beneficiaries

Within the scope of the Recovery and Resilience Plan, two types of beneficiaries are responsible for carrying out the projects and using the funding provided. Due to their similar role, the reference to these two types of beneficiaries has been simplified and unified under the term "Beneficiary".
The two types are::
  • Direct Beneficiaries are those whose funding and projects to implement are part of the Recovery and Resilience Plan that has been negotiated and approved by the European Union;
  • Final Beneficiaries are those whose funding and projects to implement are approved following a selection process through Calls for Applications.

Call for applications

As part of the Call for Applications, submissions are requested to select the projects and final beneficiaries to whom funding will be awarded. Specific selection criteria are defined for each call, which must be reflected in the applications submitted and assessed.

The project is appraised on the basis of its compliance with the selection criteria laid down in the calls for applications, and a final score may be awarded, where applicable.

Final evaluation score

9,3
Important note

The components for calculating the assessment score can be found in the selection criteria document mentioned below.

Selection criteria

The funding selection criteria to which this project and its final beneficiary were subject and its score can be found in detail on the Recuperar Portugal platform.

Beneficiaries

Intermediate beneficiaries

Beneficiaries

Procurement

Beneficiaries representing public entities implement their project by signing one or more contracts with suppliers for goods or services through public procurement procedures.

To ensure and provide the utmost transparency in all these contracts, a list of the contracts that were signed under this project is available here, along with the information available on the Base.Gov platform. Please note that, according to the legislation in force at the time the contract was signed, some exceptions do not require the publication of the contracts signed on this platform, and, therefore, no information is available in such cases.

Geographic distribution

123,39 thousand €

Total amount of the project

Where was the money spent

By county

1 county financed .

  • Lisboa 123,39 thousand € ,
Source EMRP
10.02.2026
All themes
Transparency without leading