Applications for this job are now closed
The Met Office is delighted to open our advertising for a number of progressive industrial placements, which will commence from July 2022 until July 2023.
We are hiring for an Forecasting and Observations Industrial Placement 2022 to be based in Exeter with hybrid working with a salary of £17,900 plus amazing benefits.
Why should I choose the Met Office?
- Flexible hours and homeworking (where business requirements allow)
- Our Industrial Placement scheme
- 27.5 days annual leave (plus bank holidays) and an option to buy or sell up to 5 days per year of annual leave
- Access to discounted shopping on a range of retail, leisure and lifestyle categories
Who we are
Right across the world, every single day, people make decisions based on the weather. We have a strong purpose and provide critical weather and climate science services, helping people make better decisions to stay safe and thrive.
Everything we do is based on world-leading science and enhanced by the close working relationships we have with partner organisations around the globe. We collect and make sense of massive amounts of data every day, using cutting-edge technology for the benefit of mankind - and our planet.
Our exceptional people deliver scientific, technological and operational expertise and provide critical services. Our people work together to deliver extraordinary impact, making us one of the most trusted forecasters in the world.
Our Industrial Placement Programme offers ambitious, capable under-graduates the opportunity to gain valuable experience working alongside diverse and highly skilled experts in their field. You’ll be working on projects that really matter and will make a difference. The Programme also opens up opportunities in the future after you graduate.
Our values – it’s who we are:- We’re a force for good- We’re experts by nature- We live and breathe it- We’re better together- We keep evolving
We are the Met Office, come and join us and help us to make a difference.
Job Purpose
This is an exciting opportunity to join the Met Office on a 12-month industrial placement, which will give you an opportunity to gain valuable experience working alongside diverse and highly skilled experts in their field, supporting you to achieve key deliverables and develop your own skills and knowledge. The placement will be fully integrated with your university requirements to ensure you gain the most value possible from your experience with us. You will have the opportunity to network with our cohort of Industrial Placements all over the Met Office and understand what career opportunities we can offer you after your degree.
You will join the Remote Sensing and Airborne Observations Research and Development team to undertake one of two projects (of your choice). Both projects involve using data from our new lightning location system called LEELA, and are likely to apply machine learning (ML) techniques to do one of two things:
Project 1: Sudden Ionospheric Disturbances (SIDs). This project is to improve our techniques to detect SIDs caused by solar flares using very low frequency (VLF) signals picked up by our lightning location system, LEELA. A ML pilot study began to create an extensive set of measurements of ionospheric behaviour over time (as the background for identifying events). These may help in inferring D region altitude, which would improve lightning detection accuracy. It will also help give us an improved understanding of this under-studied ionospheric region, and this could lead to improved forecasting of space weather events.
Combining data from the sensor network will allow phase difference measurements of the ionosphere in normal conditions, which could provide an initial training set for any new sensor. This can allow the use of lightning data to help map the areas of the ionosphere outside of the transmitter to sensor paths. ML may assist in classification of lightning types, and indicators of development of storms; we have recently determined there is a change in signal with local storm activity. Similar methodology may be able to be applied to other transmitter sources, such as satellite navigation and digital terrestrial broadcasts, potentially yielding additional information about the atmosphere. The objectives of this project to further explore these options with the potential to start development of an operational system, as well as present and publish the results for the benefit of the wider scientific community.
Project 2: Lightning Classification. The idea behind this project is to use distinct patterns in the lightning data from ML wavelet transforms (fingerprinting) or ML waveform data to learn more about the type of lightning we are measuring. Some initial work has already been on this by Sheffield University, which you will be able to use as starting point.
The nature of the LEELA network means that the temporal measured signals are highly variable and have been transformed during their progress through the atmosphere (which can be thousands of km). Therefore, it is not a trivial task to identify the different aspects of the lightning strike. This kind of multivariable classification space, is an ideal candidate for a machine learning approach.
The objective of this project is to create a useable training dataset (from data that already exists). To provide additional information for a given lighting strike. This should prioritise distinguishing between cloud to ground and cloud to cloud lightning (or where the LEELA team identify spikes in their AGILE development that may have some application from Machine Learning). A method which can provide a confidence of type in near real time.
There is scope for the successful candidate to shape what the project looks like, and you will be fully supported by a team of scientists and software engineers throughout your placement.
Essential Qualifications, Skills & Abilities
- You must be studying for an undergraduate degree
- Proficient in Python Programming, either in a Linux or a Windows environment.
- Strong background in maths and/or a physics.
- Ability to communicate effectively and build relationships.
- Ability to work effectively as part of a team and on your own.
- Demonstrate a pro-active approach to work and solving problems.
- Enthusiasm to undertake training and development to enhance your skills and scientific knowledge where it will help the project.
How to apply
If this opportunity excites you to join us and make a difference, click the link below and attach your cv and a cover letter. You should use your cover letter to evidence how you meet our essential criteria.
We are accepting applications until 23:59 on 18th February 2022. You will hear from us after this date to let you know if you have been shortlisted for an interview. Our interviews are taking place remotely via Microsoft Teams.
