The goal of this research is to evaluate how Large Language Models (LLMs) can be leveraged to address forecasting challenges in the energy sector, specifically those that can be framed as sequence-to-sequence problems.
The grant holder will explore different strategies on prompt engineering, compare the potential of different LLM’s and create a methodology that can be replicable to multiple challenges for the energy sector.
Academic Qualifications
* Electrical Engineering, Informatics, Computer Science or similar courses
* Programming experience in Python.
* Basic understanding of machine learning concepts.
* Experience using data science tools (e.g., pandas, scikit-learn, matplotlib).
* Familiarity with version control systems (Git)
Preference factors
* Familiarity with Large Language Models (e.g., Mistral, LLaMA).
* Understanding of machine learning workflows and forecasting methods.
* Python oriented to data manipulation and analytics.
What we offer
* Multicultural and collaborative environment
* A multicultural, international and collaborative environment that makes it easier to exchange ideas, work in networks and create synergies.
* International projects
* The possibility of working in international projects with some of the most important companies in the field.
* Mentoring with the best researchers in the fields of electrical and industrial engineering, bioengineering, information technology and physics.
* Self Improvement
* The possibility of participating in international conferences, workshops, seminars and vocational training.
* Other Benefits and Perks
* Flexible working time, health insurance, discounts in hotels, transportation, etc.
We are an equal opportunities employer and welcome applications from all qualified candidates.
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