Researcher 1 will apply mixed social science methods to explore the influence of trust on the speed of deployment of clean energy and industrial decarbonization infrastructure. This work will explore the influence of both vertical and horizontal trust between and among the diverse array of stakeholders variously engaged in or impacted by the energy transition. Researcher 1 will also extend existing work on a structure risk assessment framework help government agencies develop, monitor, and adapt... more details
Researcher - Temporary
Requisition #2024-19360
Date Posted12 hours ago(6/28/2024 10:08 AM)
Department
Andlinger Cntr for Energy/Env
Category
Research and Laboratory
Job Type
Temporary
Overview
The Andlinger Center for Energy and the Environment at Princeton University is seeking applications for two temporary research positions open in Chris Greig’s research group. The research is interdisciplinary and focused broadly on understanding and overcoming speed limits on the deployment of clean energy and industrial decarbonization infrastructure.
These positions include opportunities to learn and develop research skills and receive professional mentorship. All candidates must have a strong research background and enjoy working in teams.
We are interested in receiving applications from members of groups that have been historically underrepresented in relevant science and engineering fields. The work location for this position is in-person on campus at Princeton University.
Responsibilities
Researcher 1 will apply mixed social science methods to explore the influence of trust on the speed of deployment of clean energy and industrial decarbonization infrastructure. This work will explore the influence of both vertical and horizontal trust between and among the diverse array of stakeholders variously engaged in or impacted by the energy transition. Researcher 1 will also extend existing work on a structure risk assessment framework help government agencies develop, monitor, and adapt energy transition implementation plans. This position is part time with expectations for one to two days per week, and may be performed remotely.
Researcher 2 will apply computer science and software engineering methods to create a critical path plan for the development and deployment of the many thousands of clean energy and industrial decarbonization assets that must be deployed to achieve net-zero emissions. The research will develop algorithms to bridge idealized macroscale energy systems models with real world infrastructure development and deployment characteristics. Representative investment decision criteria and construction sequences, along with interdependencies between sectors, will be captured to generate compliant deployment sequences. Ultimately these algorithms will be used to determine more realistic transition pathways and to explore the impact of policy interventions to speed up the transition. This position is part time with expectations of three to five days per week, and may be performed remotely.
Qualifications
All candidates must have a strong research background and enjoy working in teams.
Applicants must apply online and include your CV/resume, a cover letter, and contact information for two references.
Be advised that you will be contacted only if there is further interest in your application. Your candidate dashboard may not display status updates for this requisition.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. KNOW YOUR RIGHTS
Standard Weekly Hours
0.00
Eligible for Overtime
Yes
Benefits Eligible
No
Probationary Period
N/A
Essential Services Personnel (see policy for detail)
Job Abstracts is an independent Job Search Engine. Job Abstracts is not an agent or representative and is not endorsed, sponsored or affiliated with any employer. Job Abstracts uses proprietary technology to keep the availability and accuracy of its job listings and their details. All trademarks, service marks, logos, domain names, and job descriptions are the property of their respective holder. Job Abstracts does not have its members apply for a job on the jobabstracts.com website. Additionally, Job Abstracts may provide a list of third-party job listings that may not be affiliated with any employer. Please make sure you understand and agree to the website's Terms & Conditions and Privacy Policies you are applying on as they may differ from ours and are not in our control.
Any time you conduct a search, the system shows you job matches, ranked by their Relevance Score (RS).
The score is calculated by a proprietary algorithm that uses Intelligent Machine Learning.
The Relevance Score tells you how well the job opportunity matches your search term or terms.
When not logged in, the system is limited to one search term. Scores for single term matches are usually lower.
When you register, log in, and set up multiple terms prioritized by importance, the jobs found for you will receive a much higher Relevance Score.