Degree Project: Climate action: Making data widely available
About the company
ÅF Pöyry is an international leader within engineering, design and advisory services. We create solutions to support our customers worldwide to act on sustainability as well as the global trends of urbanisation and digitalisation. We are more than 16,000 devoted experts within the fields of infrastructure, industry and energy operating across the world to create sustainable solutions for the next generation.
About the job
MASTER'S DEGREE PROJECT FOR SPRING 2020
It's time for degree projects! ÅF will offer several degree projects and will present them at ICES Degree Project Fair on Wednesday 2nd October and KTH's Degree Project Fair on Wednesday 9th of October. Sounds interersing? Apply by sending in an application through the ad. You can easily apply with your LinkedIn profile. As a part of the selection process there might be a test and you will be invited to ÅF's head office in Solna to get to know us better and the degree projects.
This project is carried out at ÅF with a supervisor from ÅF.
Degree Project: Climate Action: Making data widely available
AI and ML has been used in a wide variety of areas such as robots performing perilous tasks, self-driving vehicles, chess playing computer programs etc. However, perhaps at present, AI has especially gained momentum with regards to “big data”. AI is able to adapt by using learning algorithms, and can be used to interpret large amounts of data, hence new patterns, information and conclusions can be discovered. By using AI, tasks can be performed that are too difficult for humans.
ÅF has previously been working with a project called Interact II, supporting a large research network focusing on environmental changes in the Arctic. During 2020 the new Interact III project will begin, which will utilize AI and ML to deliver new results for the research community as well as for the markets or any interests outside this area.
Environmental change in the Arctic is extremely complex and diverse. Although academia has made great progress in documenting change, it is now accepted that “there are many ways of knowing”. In addition to conventional and traditional knowledge, there are many hidden resources on environmental change. These include private photographs, landscape paintings, limited circulation expedition reports, ships’ captains’ log books and harbor master records of harbor ice etc. Often, these resources extend the records on environmental change in the Arctic back in time before satellites and sometimes before research stations were established.
Ultimately, it is the aim that cooperation between representatives from science and relevant manufacturers should lead to new businesses, methods, products and/or technology. This type of information is relevant to industries such as the forest industry, conservation organizations, local and Indigenous communities, national parks, the tourist industry and other stakeholders within the Arctic region not yet aware of this “hidden” data resources available.
As the project will begin in January 2020 there are a few options on how the master thesis can be aligned. However, one main task is likely to be to do a pre-study on inquires and needs from station managers and researchers that will identify possible datasets and types of questions to be answered.
Another important task will be to identify the AI technology trends and AI algorithms used specifically for environmental research and in general the latest technologies within machine learning (ML) and artificial intelligence (AI)
- Discover examples of old resources in text and/or image format and use breaking science technology to demonstrate some aspects of environmental change over long periods combining this data with conventional data.
- Increase awareness among station managers of ground breaking methods such as machine learning, what they can achieve and the prerequisites for using them.
One of the initial tasks for the work package and the master thesis work will be to work closely with station managers and scientists to retrieve historical archived data (e.g. derived from photos, paintings, maps and reports) and to identify and classify it as well as find solutions to transfer and store relevant information needed to be processed. If necessary, the process may also use data retrieved from various modern technologies such as satellite and aerial images or other sensor data.
Who are you?
The thesis is at master's level (30HP) scheduled to be started by Q1 (P3-P4) 2020, suitable for two persons and will be performed mainly at ÅF's head office in Solna.
This degree project will require that you have knowledge within:
- Familiarity with basic machine learning, AI techniques such as Regression, Clustering and Artificial Neural Networks.
- Comprehension and knowledge of DSP basics and Data Analysis.
- Python, NumPy and preferably some familiarity with Tensorflow.
- A passion for the environment and sustainability.
- Project management skills.
Latest day to apply is monday 14/10-2019. The selection process is ongoing, so submit your application today since the degree project can be filled before last application day.
The ÅF Group is ranked as one of Sweden’s most popular employer among engineers. At ÅF you will be involved in developing innovative and sustainable solutions within infrastructure, energy and industry. We are always looking for the sharpest skills that can create a future society together with us. We hope you will learn as much from us as we will learn from you.
When doing your master thesis at ÅF you will be a part of our business, participate in internal activities, get to know other ÅF consultants and see what we do for our customers.
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