关于职务
- 国家: Germany
- 州/省/县: Berlin
- 城市: Berlin
- Conduct original, high-impact research in foundation models, specifically tailored for power grid data modalities and applications. Spearhead the development of novel deep learning architectures, algorithms, and training methodologies tailored for these.
- Deeply investigate and advance pioneering research in relevant areas adapting and integrating methods and techniques from other public research
- Collaborate closely with AI engineers and domain authorities to translate research breakthroughs into practical, scalable solutions deployable within real-world power grid systems.
- Build and mentor a high-performing research team, fostering a collaborative and innovative research culture within the newly formed AI lab as well as drive rapid iteration and proof-of-concept (PoC) development to quickly validate research ideas
- Optimally communicate research findings to both technical and non-technical audiences (via technical blogs or publications in conferences and journals), and represent the lab externally at conferences and industry events
- Lead research projects independently, showcasing strong initiative, problem-solving abilities, and a proactive attitude.
- Strong expertise and prior experience with building foundation models and other related concepts, with direct prior experience in at least one of the following highly desired - AI for Simulation/AI for Physics, Neural Operators, GNNs, Transformers, etc.
- Proven track record to design, develop, and implement novel deep learning architectures and algorithms and experience scaling solutions involving large datasets and complex models, applying large compute clusters.
- Strong ability to work independently, rapidly iterate on ideas, and quickly develop and validate proof-of-concepts.
- Excellent communication, presentation, and teamwork skills, with the ability to lead and inspire a research team and collaborate effectively with diverse collaborators.
- Master's or Ph.D. in Computer Science, Electrical Engineering, Physics, Mathematics, or in a related quantitative field, or equivalent industry experience with a strong demonstrable research background in AI/ML.
- Long term research experience in deep learning, machine learning, or related areas, with a focus on developing and scaling innovative AI solutions.
Bonus Points - Prior experience in a top AI research lab
- Contributions to open-source machine learning projects.
- Experience applying AI/ML to power systems, electrical grids, or related domains.
- Publications in top-tier AI conferences and journals.
At Siemens Energy, we are more than just an energy technology company. With ~100.000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.
Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.
- In addition to an attractive remuneration package in line with the market, you can expect an attractive employer-financed company pension scheme
- We also offer the opportunity to become a Siemens Energy shareholder
- We offer our employees the opportunity to work flexibly and remotely, and our inspiring offices provide space for collaboration and creativity
- The professional and personal development of our employees is very important to us. We provide them with the opportunities to learn and develop in a self-determined way, various attractive programmes and learning materials are available for this purpose
- In relation to the "compatibility of family and work", we have a wide range of offers, e.g. flexible working time models, childcare places at many locations, the possibility of trial part-time work or even a sabbatical