A 3-year PhD fellowship in sustainability science is offered by National Institute for Aquatic Resources (DTU Aqua) at Technical University of Denmark).
You will develop fundamental concepts in the emerging field of computational human ecology to understand how people interact with nature and the benefits they derive from those interactions. The student will have the opportunity to develop ground-breaking work, in collaboration with industry, to assess global human-nature interactions from social media observations and derive insights about their well-being benefits and sustainability.
This work will have direct applications by developing approaches to integrate the value of nature-based recreation and tourism in broad aspects of nature governance.
Responsibilities and qualifications
The successful candidate will use longitudinal studies of social media observations (Facebook, Twitter, Flickr, Reddit) to estimate natural environment features that attract people to nature-based recreation and tourism. You will assess the overlap between the use of those features (such as species and habitats) and their sensitivity to recreation and tourism using the IUCN Red List assessments. You will also assess how reported nature exposure is associated with changes in wellbeing indicators that can be derived from social media observations.
As part of this project, you will work in collaboration with the Facebook Data For Good Programme to expand insights about nature use that can be derived from the Programme’s tools and data with the aim to propose new insights tools that can be made available to other researchers through the Programme.
You will have the opportunity to complement this longitudinal work with experimental manipulations of wildlife tours, in collaboration with the Pacific Whale Foundation and PacWhale Eco-adventures in Hawaii. These experiments will estimate changes in wellbeing proxies, estimated using wearable devices, depending on controlled variation in tour features. The aim will be to understand functional processes involved in the way nature exposure might elicit wellbeing benefits.
For this project we are looking either for a student with a good data science and machine learning background who will be trained by the supervisor in ecological sciences and statistical modelling, or for a student with an ecological modelling background who will be trained by the supervisor in data science, particularly machine learning methods.
You must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree.
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.
Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.
Starting Date will be mutually agreed with the successful candidate in the first half of 2022.
You can read more about career paths at DTU here.
Is available from Professor David Lusseau, DTU Aqua, email@example.com, https://orbit.dtu.dk/en/persons/david-lusseau and https://www.researchgate.net/profile/David-Lusseau-2
You can read more about DTU Aqua at https://www.aqua.dtu.dk
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.
Your complete online application must be submitted no later than 1 December 2021 (Danish time).
Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link “Apply online”, fill out the online application form, and attach all your materials in English in one PDF file. The file must include:
- A letter motivating the application (cover letter)
- Curriculum vitae
- Grade transcripts and BSc/MSc diploma
- Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)
- 2 letters of recommendation
You may apply prior to obtaining your master’s degree but cannot begin before having received it.
All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.