Research Assistant, Urban Physics/ Tutkimusapulainen, rakennustekniikka

at  Tampereen yliopisto

RESEARCH ASSISTANT, URBAN PHYSICS/ TUTKIMUSAPULAINEN, RAKENNUSTEKNIIKKA

Tampere University and Tampere University of Applied Sciences create a unique environment for multidisciplinary, inspirational and high-impact research and education. Our university community has its competitive edges in technology, health and society. www.tuni.fi/en
The way our urban areas are designed influences the amount of energy we consume, our exposure to environmental hazards such as pollution and climate change, and our health. The Urban Physics Research Group at Tampere University uses data analysis, engineering and physic-based modelling approaches to study how to design cities that are sustainable and healthy, now and in the future.

JOB DESCRIPTION

We are looking for a talented and motivated Research Assistant to provide parental leave cover for the Academy of Finland – funded T-Winning Spaces 2035 project. The T-Winning project aims to increase understanding about the environmental and social impacts and challenges of digital remote work, and provide winning spatial solutions and strategy, policy and management recommendations for different types of organizations and individuals.
Your role in the project will be to help understand – and quantify - the environment and health implications of the digital and green transition. You will work to support the modelling of GHG and air pollution emissions, changes to population behaviours and exposure to environmental hazards like air pollution for various digital working scenarios in Finland. You will then work to produce simplified estimates of these impacts, based on this synthesis using modelling approaches.
As an employer we are committed to promoting diversity within our team and would like to encourage all interested applicants, irrespective of their backgrounds to apply!

REQUIREMENTS

We appreciate the following:

• Proficiency in Python, with a good understanding of mathematical modelling and experience with data analysis
• Background in engineering, data science, and mathematical modelling. Knowledge of transport modelling is an advantage
• Master level studies desirable
• The candidate should work well in an international, collaborative research group. The working language will be English

Please refer the Job description for details