**Job Description**
This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms to cope with the challenges of high price volatility and uncertainty in short-term energy markets, driven by the shift towards intermittent energy sources. The algorithms will leverage real-time data to continuously adapt to market dynamics and make economically viable trading decisions by optimally utilizing assets such as grid-level battery storage and electrolyzers. The role involves collaboration with the HBE department and an industrial partner, offering exposure to the energy sector’s trading floor.
**Skills & Abilities**
• Affinity and/or experience with computer programming, statistical learning, and optimization techniques.
• Good team spirit.
• Ability to conduct independent research within an ongoing project.
• Willingness to develop skills in coding, writing, and publishing.
• Strong passion and outstanding skills in algorithmic design.
• Good communication skills.
• Excellent command of English.
**Qualifications**
Required Degree(s) in:
• Operations Research
• Computer Science
• Mathematics
• Industrial Engineering
• Related discipline
**Experience**
Other:
• English proficiency (IELTS total band score of at least 6.5, Internet TOEFL test (TOEFL-iBT) score of at least 90, or Cambridge CAE-C/CPE) for applicants with non-Dutch qualifications and no secondary/tertiary education in English.
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