Machine Learning Intern
vor 4 Monaten
Your Role
In the rapidly advancing field of material science, accurately predicting the early lifetime and structural stability of catalysts is crucial for applications in energy storage, sensors, and catalysis. Traditional methods of evaluating catalyst stability are often time-consuming and costly. Graph Neural Networks (GNNs), which can model complex relationships between atoms in a material, offer a groundbreaking approach to predict these properties effectively. At Dunia, we are pioneering the integration of GNNs with material informatics to accelerate the discovery and optimization of catalysts with enhanced stability and performance. This internship presents a unique opportunity to contribute to cutting-edge research focused on predicting the early lifetime and stability of catalyst structures, utilizing advanced artificial intelligence (AI) techniques.
Our company
Dunia is at the forefront of the race to create a sustainable future for our planet. With a mission to invent breakthrough clean energy materials, we use the latest AI tools and chemical robots combined with our scientific expertise to build a “self-driving laboratory” that can discover new active materials faster than ever before. Targeting the toughest industry sectors such as shipping and aviation, we are developing sustainable processes to reduce CO2 emissions by over 2.1 billion tons per year. We named our company 'Dunia', because it means 'world' in over 20 languages. We want to both positively impact the world AND create an inclusive environment where the world’s brightest come together to solve humanity's biggest challenges.
Tasks- Develop and apply i.a. Graph Neural Network models aimed at predicting the early lifetime and structural stability of catalysts.
- Identify and define new descriptors for catalysts that can be integrated into these models, thereby enhancing their prediction accuracy.
- Apply data mining techniques to explore trends, patterns, and correlations within the database, ultimately developing predictive models for screening new catalyst compositions.
- Documente your research process, methodologies, and results, and expect to prepare detailed reports and presentations to effectively communicate your findings to the research team and broader audience.
- Collaboration will be key, as you will work closely with other researchers, data scientists, and engineers to integrate material informatics approaches into ongoing projects.
- Participate in team meetings, seminars, and workshops, where you will have the opportunity to share your knowledge and learn from others.
- We are looking for a motivated and enthusiastic intern with a passion for AI4Science and AI4Climate
- The ideal candidate will be currently pursuing a Master's or PhD degree in Computer Science, Materials Informatics, Chemistry, Physics, Computational Science, or a related field.
- Good level in programming as well as basic understanding of machine learning or graph theory is expected.
- Experience in material modeling, computational chemistry would be a plus.
- 30 days paid holiday🌴
- Design your own perks 🚇🎫🏋️♀️
- Mentorship to help you grow into the roles you want 🎯
- Awesome colleagues & regular company events 🙌
- Flexible working hours & hybrid working ☕
- Aiding the process of VISA application for non-EU citizens 🌎
Do not worry if you do not tick all the boxes. Do not exclude yourself from amazing opportunities by not applying. We strive to create a diverse and inclusive workplace where everyone feels welcome and safe to be their authentic self. Non-traditional career paths are welcome and valued. If you share our vision, you can be certain that we want you to succeed. You might be just the right candidate for this or for other roles that have not opened yet. Reach out
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