ZZ004413 - Research Fellow in the Logistics of Offshore Wind Farms
xDepartment of Mathematicsx

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Faculty of Technology

Department of Mathematics

 

Research Fellow in the Logistics of Offshore Wind Farms

 

Employment type:  Fixed-term contract (to 30 June 2019)

Salary:  £34,520 - £37,706 per annum

Post number:  ZZ004413

Date published:  08 January 2018

Closing date:  18 February 2018

 

Interview date:  26 February 2018

 

Applications are invited for the position of Research Fellow in the Logistics, Operational Research and Analytics (LORA) Group in collaboration with the Institute of Industrial Research at the University of Portsmouth.  The researcher will work on a collaborative multi-disciplinary project funded by Innovate UK, partnering with the following: LORA Group, Institute of Industrial Research at the University of Portsmouth, ASV Unmanned Marine Systems, Houlder Ltd, Offshore Renewable Energy Catapult, and SeaRoc Group.

 

The vision of the project is to undertake industrial research to characterise the issues, potential cost savings and critical areas for development to enable autonomous vessels to be used for parts supply and crew transfer for maintenance in offshore renewables, to reduce the cost of energy, reduce health and safety risks. The specific role of the University of Portsmouth in this project is to develop on-board AI health diagnostics algorithms for autonomous vessels; and real-time routing and scheduling models and algorithms for optimal allocation of available vessels and their routes for spare parts distribution with respect to minimum fuel consumption (fuel efficiency), minimum time underway, or any desired combination of these factors. The optimisation models and algorithms will take into account real-time information on forecasts of weather and sea conditions, vessel's individual characteristics for a particular transit, cargo load, frequency of transport, availability and capacity of the vessels.   

 

Applicants should have a PhD (or equivalent research experience) in Operational Research, Logistics, Artificial Intelligence, or a related discipline. Experience in the logistics of offshore wind farms is desirable. Ideally, you should have experience in dealing with industrial and/or governmental problem owners and decision makers. Excellent algorithm development and coding skills are essential for this position. The applicants should show strong motivation for independent research, and the ability to work with academic and industrial partners.

 

Applicants should also be able to perform effectively under pressure and time constraints, possess good organisational and time management skills, pay close attention to detail, and have effective interpersonal skills. Applicants should be willing to undertake travel to work with the partners.

 

Informal enquiries can be addressed to Prof. Djamila Ouelhadj (Djamila.ouelhadj@port.ac.uk), tel: +44 (0) 23 8059 6355, mobile: +44 (0)7818453756; or Prof. David Brown (david.brown@port.ac.uk), tel: +44 (0)7831631672.

 

For detailed information about the vacancy, please select this link:ZZ004413 - Research Fellow in the Logistics of Offshore Wind Farms.docx

Vacancy Description
-
 

Faculty of Technology

Department of Mathematics

 

Research Fellow in the Logistics of Offshore Wind Farms

 

Employment type:  Fixed-term contract (to 30 June 2019)

Salary:  £34,520 - £37,706 per annum

Post number:  ZZ004413

Date published:  08 January 2018

Closing date:  18 February 2018

 

Interview date:  26 February 2018

 

Applications are invited for the position of Research Fellow in the Logistics, Operational Research and Analytics (LORA) Group in collaboration with the Institute of Industrial Research at the University of Portsmouth.  The researcher will work on a collaborative multi-disciplinary project funded by Innovate UK, partnering with the following: LORA Group, Institute of Industrial Research at the University of Portsmouth, ASV Unmanned Marine Systems, Houlder Ltd, Offshore Renewable Energy Catapult, and SeaRoc Group.

 

The vision of the project is to undertake industrial research to characterise the issues, potential cost savings and critical areas for development to enable autonomous vessels to be used for parts supply and crew transfer for maintenance in offshore renewables, to reduce the cost of energy, reduce health and safety risks. The specific role of the University of Portsmouth in this project is to develop on-board AI health diagnostics algorithms for autonomous vessels; and real-time routing and scheduling models and algorithms for optimal allocation of available vessels and their routes for spare parts distribution with respect to minimum fuel consumption (fuel efficiency), minimum time underway, or any desired combination of these factors. The optimisation models and algorithms will take into account real-time information on forecasts of weather and sea conditions, vessel's individual characteristics for a particular transit, cargo load, frequency of transport, availability and capacity of the vessels.   

 

Applicants should have a PhD (or equivalent research experience) in Operational Research, Logistics, Artificial Intelligence, or a related discipline. Experience in the logistics of offshore wind farms is desirable. Ideally, you should have experience in dealing with industrial and/or governmental problem owners and decision makers. Excellent algorithm development and coding skills are essential for this position. The applicants should show strong motivation for independent research, and the ability to work with academic and industrial partners.

 

Applicants should also be able to perform effectively under pressure and time constraints, possess good organisational and time management skills, pay close attention to detail, and have effective interpersonal skills. Applicants should be willing to undertake travel to work with the partners.

 

Informal enquiries can be addressed to Prof. Djamila Ouelhadj (Djamila.ouelhadj@port.ac.uk), tel: +44 (0) 23 8059 6355, mobile: +44 (0)7818453756; or Prof. David Brown (david.brown@port.ac.uk), tel: +44 (0)7831631672.

 

For detailed information about the vacancy, please select this link:ZZ004413 - Research Fellow in the Logistics of Offshore Wind Farms.docx