Research Intern: Online Machine Learning for Power Grids

(HE)Remote ON, Stoney Creek

Hitachi

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Location:

Remote - Ontario, Canada

Job ID:

R0063693

Date Posted:

2024-10-29

Company Name:

HITACHI ENERGY CANADA INC.

Profession (Job Category):

Administration & Facilities

Job Schedule: 

Full time

Remote:

Yes

Job Description:

Hitachi Energy has an opening for the position of Research Intern in the field of online machine learning and its applications in power grids. The hired intern will work under the supervision of Research Scientist(s) in the Hitachi Energy Research center at Montreal, Canada. This position will be held in a hybrid-format or remotely within Canada.  

Duration of internship: Preferably 6 months.

Start and end dates are negotiable.

Mode of work: Flexible for hybrid or Remote.

Paid internship

Responsibilities:

  • Perform literature survey to explore state-of-the-art AI methodologies and their applicability, strengths, and weaknesses. Focus will be on methodologies and tools used in the domains including (but not limited to) sequential and time series data. 

  • Investigate methodologies to understand and interpret the decisions from ML models for power grid applications. 

  • Apply and modify ML methodologies to develop solutions for power grid automation. Run experiments in python, prepare codebase. 

  • Prepare a technical report, presentation on work accomplished during internship and/or publication in peer-reviewed conference. 

Minimum qualification:

  • PhD students/candidates in Electrical Engineering, Computer Science/Engineering or Applied Mathematics. Excellent senior year Master’s students with relevant experience are also welcome to apply.  

  • In-depth understanding of AI/ML methodologies required, such as: classical and deep learning based supervised/unsupervised classification/regression and associated time series models. 

  • Prior experience in technology screening through literature survey required. 

  • Prior experience in developing machine learning based solutions for academic or industrial problems required. 

  • Coding experience in Python and ML libraries (e.g., Tensorflow/Pytorch, Scipy, SkLearn) required. 

  • Good communication skills (both written and spoken). 

Good to have/preferred qualification:

If you have any of the following qualifications, please ensure to clearly mention them in your resume:  

  • Understanding and/or practical experience in one or more of the following fields preferred: continual learning, generalized learning, meta learning, scalable AI, probabilistic machine learning, lifelong learning, safe ML. 

  • Graduate-level knowledge of probability, statistical methods, or optimization preferred. 

  • Ability to do critical and innovative thinking. Ability to take lead in realizing ideas. 

  • Prior experience in writing technical articles/reports is good to have. 

  • Familiarity with power grid automation is good to have. 

More about us:

Hitachi Energy is a global technology leader that is advancing a sustainable energy future for all. We serve customers in the utility, industry and infrastructure sectors with innovative solutions and services across the value chain. Together with customers and partners, we pioneer technologies and enable the digital transformation required to accelerate the energy transition towards a carbon-neutral future. We are advancing the world’s energy system to become more sustainable, flexible and secure whilst balancing social, environmental and economic value. Hitachi Energy has a proven track record and unparalleled installed base in more than 140 countries. Headquartered in Switzerland, we employ around 38,000 people in 90 countries. In fiscal year 2020 we generated business volumes of around $10 billion USD as reported by Hitachi. www.hitachienergy.com

Only selected applicants will be contacted. 

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Tags: Classification Computer Science Deep Learning Engineering Industrial Machine Learning Mathematics ML models PhD Python PyTorch Research Scikit-learn SciPy Statistics TensorFlow

Perks/benefits: Flex hours

Regions: Remote/Anywhere North America
Country: Canada

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