Postdoctoral Fellow: Deep Learning for Hydropower Forecasting

Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID; Portugal; Presencial; EUR 19.000 - 23.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Monthly maintenance allowance €1,901.0

Descripción de la vacante

Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID in Lisbon, Portugal, invites applications for 1 Post-Doctoral Research Fellowship under the TIES project. The role focuses on probabilistic river discharge forecasting using deep learning, with tasks spanning model development, testing, and integration with electricity market data.

The fellowship lasts 12 months starting 1 January 2027, with possible renewal up to 18 months.

Formación

• PhD obtained in the last three years in a related field.
• Preferential experience in deep learning for time series and forecasting.
• Proficiency in Python and DL frameworks; English writing and speaking skills.

Responsabilidades

• Develop, train and validate deep learning models for probabilistic forecasting of river inflows and sediment transport.
• Test operational forecasting chains with performance monitoring and explainability analyses.
• Analyse electricity market variables and integrate with hydrological forecasts.
• Contribute to project deliverables and scientific publications.

Conocimientos

Deep learning experience

Time series forecasting

English proficiency

Educación

PhD in Civil, Environmental, Electrical or Mechanical Engineering, Computer Science, Physics, Applied Mathematics, or related fields

Herramientas

Python

PyTorch

TensorFlow

Descripción del empleo

Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID in Lisbon, Portugal, invites applications for 1 Post-Doctoral Research Fellowship under the TIES project. The role focuses on probabilistic river discharge forecasting using deep learning, with tasks spanning model development, testing, and integration with electricity market data.

The fellowship lasts 12 months starting 1 January 2027, with possible renewal up to 18 months.