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Post-doctoral, Doctoral and Master's degrees in oil reservoir simulation and proxy modelling


UNISIM, a research group on simulation and management of oil fields, linked to the Department of Energy, Petroleum Engineering Division of the Faculty of Mechanical Engineering of the University of Campinas (UNICAMP), in selecting candidates for Postdoctoral, Doctoral and Master to apply proxy modelling, including artificial intelligence techniques, in numerical simulation of reservoirs, uncertainty analysis and decision.


The initiative is part of an oil company project with a real dataset (fields) to speed up reservoir development and management of oilfields using numerical and proxy models.


Candidates should develop topics related to Engineering, Physics, Computing, Mathematics, Statistics, or one or more of them, including reservoir simulation and statistics, and have advanced knowledge in the English language.


Post-doctorate with a duration of 3 years to start immediately.

Master and doctorate to begin in March 2022.


Interested candidates should send the following documents to .


IMPORTANT: Inform in the subject of the e-mail: Position MFM-[POSITION], where [POSITION] should be replaced by PDRA (Post-doctoral), DR (Doctorate) or MS (Master).


  1. Complete curriculum and official academic transcript (clean, including failures), with performance coefficient (GPA) of all courses taken;
  2. A letter of interest, written in English, explaining the interest in the position and the motivation to join the research project;
  3. Two letters of recommendation;
  4. List of scientific publications, Master's Thesis (if PhD position) and Doctoral Thesis (if Post-Doctoral position).

Post-doctoral and Doctoral degrees in artificial intelligence and software development



UNISIM, a research group on simulation and management of oil fields, linked to the Department of Energy, Petroleum Engineering Division of the Faculty of Mechanical Engineering of the University of Campinas (UNICAMP), in selecting candidates to develop software and invest in his/her future talking a Post-doctoral or Doctoral course simultaneously in a promising field of study – artificial intelligence – applied to reservoir simulation, uncertainty analysis and decision.


The initiative is part of an oil company project with a real dataset (fields) for reservoir development and management of oilfields using software development skills integrated with numerical models and artificial intelligence.


Post-doctorate with a duration of 3 years to start immediately.

The doctorate is to begin in March 2022.


Interested candidates should send the following documents to .


IMPORTANT: Inform in the subject of the e-mail: Position MFM-[POSITION], where [POSITION] should be replaced by PDRA (Post-doctoral) or DR (Doctorate).


  1. Complete curriculum and official academic transcript (clean, including failures), with performance coefficient (GPA) of all courses taken;
  2. A letter of interest, written in English, explaining the interest in the position and the motivation to join the research project;
  3. Two letters of recommendation;
  4. List of scientific publications, Master's Thesis (if PhD position) and Doctoral Thesis (if Post-Doctoral position).

Closed-Loop Field Development and Management (CLFDM) was originally conceived as a combination of model-based optimization and data assimilation. The purpose of this approach is to use new information over the reservoir life-cycle to reduce uncertainties, assist decision making and improve production strategy performance.

In UNISIM group, the closed-loop development and management methodology is divided into 12 steps and can be applied in fields at any stage of development. The 12 steps include:

- Reservoir characterization under uncertainties: data gathering and uncertainty survey for model construction and calibration. Several simulation models are generated, representing the uncertainties of the reservoir. In this step, the model fidelity (simulation grid size) is analyzed in order to balance the quality of the results and the computational time.

- Long term model-based decisions: optimization of production strategy under uncertainties. Thus, there is the generation of dynamic data, such as: pressure, productions, seismic data, etc.

- Data assimilation: according to the assimilated data, the best models are selected for use in the stage of production strategy optimization. Models can be changed according to the assimilated data.



Flowchart of closed-loop reservoir development and management methodology.
Flowchart of closed-loop reservoir development and management methodology.
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