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Machine Learning Researcher
Posted on 2/1/2022
INACTIVE
Locations
Cambridge, UK
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Data Science
Research
Tensorflow
Python
Requirements
  • Make a positive global impact on climate change and society
  • Work in an interdisciplinary environment where you are always learning
  • Develop approaches which have a direct impact on electricity grid operations
  • Be part of a collaborative and sociable team
  • Join an established Machine Learning lab in a growth phase
  • You hold a PhD (or Master's degree with industry research experience) in Machine Learning, Electrical Engineering, Mathematics, Physics, Computer Science, Statistics, or other related disciplines
  • You have expertise in at least two of these topics: Bayesian methods, probabilistic modelling, optimisation, or statistical inference on complex data
  • You have experience with numerical and scientific computing concepts and methods
  • You have good coding skills, preferably with experience in Python and/or Julia
  • You have hands-on experience with implementing models within machine learning frameworks (for example TensorFlow, JAX, Flux.jl)
  • Decision-making under uncertainty
  • Time-series forecasting
  • Gaussian processes
Responsibilities
  • Design, prototype and improve the models used in our core system
  • Actively participate in research planning
  • Analyse relevant data, draw insights and communicate results to other team members
  • Collaborate on diverse projects with team members including Power Systems and Data Science Researchers, Research Software Engineers, and Developers
  • Communicate research and share knowledge internally and externally, such as in research papers and at conferences
Invenia Labs

11-50 employees

Invenia Labs uses machine learning to optimise the electricity grid.
Company Overview
Invenia is a team of scientists and engineers working together to solve key challenges that the world is facing. They focus on using machine learning to optimize complex decision making and reduce inefficiencies.