Internship in Ml Applied to Chemistry for

Vor 3 Tagen

Baden, Schweiz HITACHI ENERGY LTD Vollzeit

**Description**

**How you’ll make an impact**
- Conduct literature surveys and summarize state-of-the-art computational approaches for evaluating alternative insulating gases.
- Develop and implement machine learning models to predict key properties of potential SF6 alternatives, such as dielectric strength, global warming potential, and toxicity.
- Design and optimize algorithms for multi-objective optimization of gas mixtures, considering various parameters simultaneously.
- Implement and refine estimation methods for properties of gas mixtures, including dew points and dielectric strength.
- Analyze and interpret results, presenting findings to the research team and potentially contributing to scientific publications.
- Collaborate with interdisciplinary teams, including chemists and electrical engineers, to validate computational results.

**Your background**
- Currently pursuing a MSc degree in Computer Science, Computational Science, Applied Mathematics, or a related field - official enrollment is essential.
- Background in machine learning, optimization algorithms, and data analysis.
- Proficiency in Python; experience with scientific computing libraries (e.g., NumPy, SciPy, scikit-learn) is highly desirable.
- Familiarity with or willingness to learn concepts in computational chemistry and thermodynamics.
- Experience with version control systems (e.g., Git) and collaborative coding practices.
- Analytical skills and ability to work with complex, multidimensional data.
- Excellent communication skills in English, both written and spoken.
- A team-oriented working style and enthusiasm for interdisciplinary research.

**More about us**

This internship offers a stimulating environment where you'll contribute to cutting-edge research with real-world impact. Join us in the quest to make power systems more sustainable through innovative computational approaches

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