Siemens Energy

Master Thesis: Generative Adversarial Networks and Variational Autoencoders for Multivariate Time-Series Tasks

A Snapshot of Your Day

As a graduate student undertaking a master's thesis project at Siemens Energy, you will dive into the innovative world of Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), transforming the landscape of multivariate time-series analysis in the energy sector. Here's what to expect:

• Experimenting with GANs and VAEs to synthesize new sensor data, improving model development.

• Applying your deep learning expertise to denoise and refine operational data sets.

• Investigating and implementing data discrimination techniques to identify specific data characteristics.

• Applying advanced visualization tools like t-SNE to evaluate the quality of synthetic data.

• Collaborating with experts to align your projects with Siemens Energy's central initiatives, contributing to the acceleration of the energy transition.

How You’ll Make an Impact

Pioneering the application of GANs and VAEs to generate high-quality synthetic time-series data for use in advanced energy sector analytics. As well as, developing and refining algorithms for data augmentation, enabling the creation of expansive datasets with known characteristics for AI methods. Additionally you will:

• Apply advanced denoising techniques to improve the accuracy and reliability of sensor data, enabling better decision-making.

• Conduct detailed evaluations of synthetic data quality, ensuring that it meets the requirements for training robust AI models.

• Strong written and verbal communication skills, with the ability to articulate your work and present findings effectively.

• An attitude of collaboration, enthusiastic about working in a multidisciplinary team and incorporating feedback from various collaborators.

What You Bring

• Currently pursuing a Master’s degree or equivalent experience in Machine learning, Statistics, Computer Science, Data Science, or a related field.

• Familiarity with GANs, VAEs, and other machine learning techniques applicable to time-series data.

• A creative and analytical approach with a strong interest in synthesizing and refining data for AI applications.

• The ability to work independently while also being a great teammate in a collaborative research environment.

• Excellent problem-solving skills and the capacity to translate complex concepts into actionable insights.

• Strong communication skills to present technical findings to both technical and non-technical audiences.

About the Team 

You will get an opportunity to work with Application Platforms Business (APB) team, which is one of the teams in IT that is driving the End-to-end responsibility for all central applications and platforms. Our team focuses on solution architecture, service management and application maintenance, operational provider management, and digital consulting. 

Implementing all projects concerning central platforms. Orchestrating the governance structure of Business Partner Boards. Join us and get to know a global company in the forefront of new energy technology. During your time at Siemens Energy you will also get the opportunity to establish a network for future cooperation!

Who is Siemens Energy?

At Siemens Energy, we are more than just an energy technology company. We meet the growing energy demand across 90+ countries while ensuring our climate is protected. With more than 99,000 dedicated employees, we not only generate electricity for over 16% of the global community, but we’re also using our technology to help protect people and the environment.

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.

Find out how you can make a difference at Siemens Energy:https://www.siemens-energy.com/employeevideo

Our Commitment to Diversity

Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.

Application

Don’t hesitate – apply via https://jobs.siemens-energy.com/en_US/jobs , id nr 266224 no later than 2024-11-29! 

Ongoing selection is applied, the role might be filled before last application date.

For questions about the role, please contact Shwetha Chandramouly on shwetha.chandramouly@siemens-energy.com

For questions about the recruitment process please contact the responsible recruiter Ermina Imamovic on ermina.imamovic.ext@siemens-energy.com

We refrain from all contact with staffing and recruitment companies, or advertising brokers.

Location: Finspång

Trade Union Representatives: 
Anders Häll, Unionen, +46122-887514 
Simon Von Eckardstein, Sveriges Ingenjörer, +46122-842 24 
Jan Lundgren, Ledarna, +46122-812 33 
Mikael Malmgren, IF Metall, +4676-6958685

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