Research Associate - Mapping History
- Employer
- University of Bristol
- Location
- Bristol, United Kingdom
- Salary
- £33,797 - 38,017
- Closing date
- May 22, 2021
View more
- Sector
- Science, Computer Science and IT, Computer Science, Art and Humanities
- Hours
- Full Time
- Organization Type
- University and College
- Jobseeker Type
- Academic (e.g. 'Lecturer')
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The role
We invite applications from data scientists, computer scientists, or geographers/economists specialised in machine learning and computer vision for a pre-doctoral position at the University of Bristol (1 year, starting as soon as possible, with the possibility of a contract extension).
The post holder will work on the MAPHIS project (Mapping HistoryWhat Historical Maps Can Tell Us About Urban Development) which intends to develop novel, interdisciplinary methods that facilitate the extraction of information from historical maps to study the evolution of land use patterns and urban growth. One output will be the digitisation of exceptional cartographic resources (e.g., the well-known OS maps covering England and Wales from 1880-1960).
Specifically, the proposed research will use visual recognition algorithms to:
The project is an international collaboration of economists with a strong interest in quantitative methods involving: Yanos Zylberberg (Bristol, PI), Laurent Gobillon (PSE-CNRS, France PI), Stephan Heblich (Toronto, Canada PI), Pierre-Philippe Combes (ENS Lyon, Co-I), Marcel Fortin (Toronto, Co-I), Steve Redding (Princeton), Gilles Duranton (Wharton UPenn).
The project is funded by Open Research Area (ORA) for the Social Sciences ANR-DFG-ESRC-SSHRC.
What will you be doing?
The successful candidate would be expected to support the research project MAPHIS: Mapping HistoryWhat Historical Maps Can Tell Us About Urban Development, an international collaboration between researchers in the UK, France, Canada and the United States (see description below). The position would be hosted by the School of Economics at the University of Bristol, where the candidate would benefit from an interdisciplinary, international research environment, and would be able to pursue own research interests.
You should apply if
The ideal candidate will hold a MSc/MRes (or be an exceptional BSc student)-or be close to completion-in a relevant field (computer science, data science, or economics/economic geography) and should have experience/knowledge in developing machine-learning classification techniques for visual recognition.
For further information please contact Yanos Zylberberg: yanos.zylberberg@bristol.ac.uk
We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.
We invite applications from data scientists, computer scientists, or geographers/economists specialised in machine learning and computer vision for a pre-doctoral position at the University of Bristol (1 year, starting as soon as possible, with the possibility of a contract extension).
The post holder will work on the MAPHIS project (Mapping HistoryWhat Historical Maps Can Tell Us About Urban Development) which intends to develop novel, interdisciplinary methods that facilitate the extraction of information from historical maps to study the evolution of land use patterns and urban growth. One output will be the digitisation of exceptional cartographic resources (e.g., the well-known OS maps covering England and Wales from 1880-1960).
Specifically, the proposed research will use visual recognition algorithms to:
- detect points of interest, street names and labels on manuscript maps from the late 19th century/20th century, which will help draw a uniquely detailed picture of changes in the socio-economic structure and organisation of cities during the structural transformation of the economy.
- classify colour-coded information from fire insurance maps and study the horizontal/vertical growth of large cities.
The project is an international collaboration of economists with a strong interest in quantitative methods involving: Yanos Zylberberg (Bristol, PI), Laurent Gobillon (PSE-CNRS, France PI), Stephan Heblich (Toronto, Canada PI), Pierre-Philippe Combes (ENS Lyon, Co-I), Marcel Fortin (Toronto, Co-I), Steve Redding (Princeton), Gilles Duranton (Wharton UPenn).
The project is funded by Open Research Area (ORA) for the Social Sciences ANR-DFG-ESRC-SSHRC.
What will you be doing?
The successful candidate would be expected to support the research project MAPHIS: Mapping HistoryWhat Historical Maps Can Tell Us About Urban Development, an international collaboration between researchers in the UK, France, Canada and the United States (see description below). The position would be hosted by the School of Economics at the University of Bristol, where the candidate would benefit from an interdisciplinary, international research environment, and would be able to pursue own research interests.
You should apply if
The ideal candidate will hold a MSc/MRes (or be an exceptional BSc student)-or be close to completion-in a relevant field (computer science, data science, or economics/economic geography) and should have experience/knowledge in developing machine-learning classification techniques for visual recognition.
For further information please contact Yanos Zylberberg: yanos.zylberberg@bristol.ac.uk
We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.
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