About the Job
For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.
Life cycle assessment (LCA) is an important tool for sustainable decision-making. In the last decades, there was large progress in terms of the number, complexity and accuracy of impact categories covered; especially for those related to ecosystem quality. Â However, there are still some gaps. This includes impacts of noise and artificial lights on biodiversity that are not yet covered on a global level. This PhD will therefore aim to develop models for quantifying the impacts of noise pollution and artificial light on biodiversity (terrestrial, marine and/or freshwater) within the framework of LCA.
IndEcol is a pioneer in the development and application of industrial ecology methods, as well as the use of large data sets and scientific computing in industrial ecology. We focus on understanding resource use and environmental pollution associated with human activities, assessing the environmental aspects of different technologies and modeling society’s use of materials. IndEcol combines world-class competence in Life Cycle Assessment (LCA), Input-Output analysis (I/O), and Material Flow Analysis (MFA) with scientists’ contribution to IPCC and IPBES assessment reports, the International Resource Panel, active participation to the Life-Cycle Initiative hosted by UN Environment, and numerous publications featured in high-ranked journals. IndEcol hosts its own International MSc program and contributes to NTNU’s engineering education. The research team consisting of eight faculty members, the Industrial Ecology Digital Laboratory, and about 70 researchers, post.docs and PhD students.
More information can be found at here.
Your immediate leader is Professor Francesca Verones. Dr. Martin Dorber is co-supervisor of the candidate.
Duties of the position
- Develop models for the impact of noise on biodiversity
- Develop models for the impact of artificial light on biodiversity
- Contribute to an operational update of the LCIA method LC-IMPACT
- Test and apply the developed models in a case-study
- Dissemination of results in scholarly journals, at international conferences and for the general public
Required selection criteria
- You must have a professionally relevant background in in industrial ecology, environmental science/engineering or similar. Bachelor’s and master’s degrees in other disciplines will be considered on a case-by-case basis. In particular we are also open for applicants with a social or natural science master’s with strong computational or statistical competence.
- Your education must correspond to a five-year Norwegian degree program, where 120 credits are obtained at master’s level
- You must have a strong academic background from your previous studies and an average grade from the master’s degree program, or equivalent education, which is equal to B or better compared with NTNU’s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education.
- Master’s students can apply, but the master’s degree must be obtained and documented by the starting date
- You must meet the requirements for admission to the faculty’s doctoral program
- Motivation to get proficient in Python and to learn basics of R/MatLab.
- Interest in sustainability science and strong incentive to learn Industrial Ecology methods like LCA analysis.
- Proven analytical and computational capabilities, in courses and or/thesis deliverables
- Proven written and oral English communication skills
The appointment is to be made in accordance with Regulations on terms of employment for positions such as postdoctoral fellow, Phd candidate, research assistant and specialist candidate and Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosodophiae Doctor (PhD) in artistic research national guidelines for appointment as PhD, post doctor and research assistantÂ
Preferred selection criteria
- Completed courses in life cycle assessment and life cycle impact assessment
- Experience in geographical information systems (e.g., ArcGIS, QGIS or within Python, R)
- Documented competence in using the Python scientific computing stack (Numpy, Pandas, Jupyter Notebooks) or of another programming language used for environmental data analysis
- Knowledge of ecological concepts, preferably proven through completed courses in ecology
- Experience with data visualization
Personal characteristics
- Self-motivated, enthusiastic, and dedicated
- Motivated to solve environmental problems and advance sustainability
- Ambitious and goal-oriented
- Team player
- Excellent communication skills
Emphasis will be placed on personal and interpersonal qualities.
Offer
- Exciting and stimulating tasks in a strong international academic environment
- An open and inclusive work environment with dedicated colleagues
- Favourable terms in the Norwegian Public Service Pension Fund
- Employee benefits
Salary and conditions
As a PhD candidate (code 1017) you are normally paid from gross NOK 532Â 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 3 years with a potential extension for contribution to IPBES activities if expertise matches.
Appointment to a PhD position requires that you are admitted to the PhD programme in Engineering within three months of employment, and that you participate in an organized PhD programme during the employment period.
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The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution daily.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English.
Publications and other scientific work must be attached to the application. Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.
The application must include:
- CV and certificates
- Transcripts and diplomas for bachelor’s and master’s degrees. If you have not completed the master’s degree, you must submit a confirmation that the master’s thesis has been submitted.
- A copy of the master’s thesis. If you recently have submitted your master’s thesis, you can attach a draft of the thesis. Documentation of a completed master’s degree must be presented before taking up the position.
- Project proposal
- Name and contact information of three referees
- If you have publications or other relevant research work
If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor’s and master’s education, in addition to other higher education. Description of the documentation required can be found here. If you already have a statement from NOKUT, please attach this as well.
We will take joint work into account. If it is difficult to identify your efforts in the joint work, you must enclose a short description of your participation.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal and interpersonal qualities. Motivation, ambitions, and potential will also count in the assessment of the candidates.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment – DORA.
Further information on this opportunity can be found here.