Machine Learning Researcher
Company: Invenia Labs Limited
Job title: Machine Learning Researcher
Location: Cambridge, UK
Salary range: £45,000 - £75,000 depending on experience
Closing date for applications: 26 March 2019
Due to anticipated growth, this role will be open to a few successful candidates.
We are looking for Machine Learning Researchers to join a growing research and development team in Cambridge, UK.
Our team is composed of highly skilled and ambitious individuals, with a broad range of interests, including Machine Learning, Power Systems and Complex Systems. From creating experiments and prototyping implementations to testing and deploying promising ideas quickly and safely, our researchers work on real-world problems with a focus on understanding and improving the efficiency of electricity grids. They are also active in the wider research community by partnering with universities, publishing research papers, and attending conferences.
Main duties and job responsibilities
• Design, implement, and test models to meet research goals.
• Analyse relevant data and communicate results in the form of discussions and reports to other team members.
• Develop well organised and documented code for individual projects or general use as necessary.
• Collaborate with other researchers to meet research goals.
• Present research clearly and concisely, both verbally and in writing, for internal and external use as appropriate.
• Collaborate with and maintain relationships with external research labs, publish research papers and attend conferences.
• Keep up with the literature in the academic domain.
Mandatory qualifications, skills and experience
• Master’s degree or PhD in a relevant discipline or with a relevant major, such as Machine Learning, Electrical Engineering, Mathematics, Physics, Computer Science, Statistics or Econometrics.
• Expertise with Bayesian methods, probabilistic modelling, optimisation, and statistical inference on complex data.
• Experience and/or familiarity working with or studying numerical and scientific computing concepts and methods.
• Good coding skills, preferably experience with Python and/or Julia.
• Experience with machine learning toolboxes and frameworks, such as TensorFlow and scikit-learn.
• Previous experience in energy modelling.