Energy Systems

As AI and data centers expand, their energy demands are becoming a significant sustainability issue, with AI projected to consume 85-134 TWh of electricity by 2027—comparable to a small country's annual usage. The growing adoption of AI models like OpenAI’s ChatGPT and Google’s Bard underscores the need to reduce data centers' carbon footprints. Future AI data centers will focus on low-carbon strategies to mitigate their environmental impact.

This cross-disciplinary PhD program in electrical engineering and computer science aims to develop real-time strategies for minimizing the carbon footprint of data centers. The research will optimize the jobs scheduling at large scale data center, addressing the challenge of managing high volumes of computational tasks required by large AI models. Advanced machine learning, optimization, and data analytics techniques will be explored to enable a more proactive response to the electricity supply profile, ensuring that data center operations are effectively integrated with the broader energy network.

A key component of the program is exploring how AI data centers can support energy networks, providing grid services like frequency and demand response during periods of low-carbon electricity or when the grid requires ancillary services. This research seeks to enhance the interaction between data centers and the electricity grid, promoting better coordination and contributing to grid stability and efficiency.

The solution will focus on developing practical, low-carbon data center operations for real-world deployment. By improving demand response services, data centers can operate more sustainably while helping stabilize the grid. This research is vital for addressing the energy demands of AI systems and ensuring that future AI developments align with global sustainability goals.

To apply for this position, It will be an advantage if applicants have relevant industry or research experience, or good programming skills using Python, Julia or matlab. Strong knowledge in one or more of the following areas is highly desirable:

• Power network modelling and control

• Optimization, data science, operational research and mathematical programming.

• Machine Learning and Reinforcement Learning

• Computer science with understanding of data center structure and operation

**NOTE: There is no closing date for this position, which will remain open until filled.  Early contact is highly recommended.

Reference:

   ‘Generative AI’s Energy Problem Today Is Foundational’ https://spectrum.ieee.org/ai-energy-consumption   Misaghian, M. Saeed, et al. "Assessment of carbon-aware flexibility measures from data centres using machine learning." IEEE Transactions on Industry Applications 59.1 (2022): 70-80.   Sarkar, Soumyendu, et al. "Real-time Carbon Footprint Minimization in Sustainable Data Centers with Reinforcement Learning." NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning. 2023.

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity

Interested applicants are welcome to contact Dr Wei Sun by email for pre-application enquiries (W.Sun@ed.ac.uk).

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in Electrical Engineering, Computer Science, Mathematics, or related areas. Possibly supported by an MSc Degree.

Further information on English language requirements for EU/Overseas applicants.

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.

Further information and other funding options.

In the next decade, distributed sensor network systems made of small flying sensors, from dust-scale to insect-scale, will enable a step change in monitoring natural disasters and remote areas. They will contribute to protecting the environment by providing data on the contamination of physical and biological systems and the impact of human activities. To date, a key limitation of this technology is that small sensors can remain airborne only for a few tens of minutes.

By contrast, some natural flyers, such as the dandelion fruit, travel unpowered for days and hundreds of kilometres. Recent Edinburgh research revealed the aerodynamics underlying the extraordinary flight ability of the dandelion, including the energy scavenging mechanisms that allow it to regain altitude at every wind gust. The present project aims to exploit these aerodynamic findings to enable a step change in the endurance and range of flying sensors. The candidate will design and test an ultra-light (c.a. 1 mg) insect-scale bioresorbable flyer with sensing and communication capabilities in a bespoke wind tunnel.

The successful applicant will work in an Edinburgh team of about ten researchers, including PhD students, postdoctoral research associates, and technicians. These researchers contribute to the design of this novel technology through numerical simulations, experiments, and theoretical model development. The Edinburgh team also collaborates closely with several overseas research leaders who undertake complementary projects and advise on the team's activities.

Successful applicants should have a bachelor’s degree in engineering or equivalent experience and be passionate about microtechnology and robotics, or aerodynamics; the project will be tailored to the specific field of interest of the student.

The position will remain open until a successful applicant is identified. For informal enquiries, please email Dr Jawahar Sivabharathy Samuthira Pandi, jsamuthi@ed.ac.uk. We aim to reply to all informal enquiries within 10 working days. 

 For more information, visit https://voilab.eng.ed.ac.uk/home 

https://VOILAb.eng.ed.ac.uk

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.

For more information on funding opportunities, please visit here: https://eng.ed.ac.uk/studying/degrees/postgraduate-research/phd-scholarships 

For the first time, the America's Cup was sailed with foiling boats in 2013. This led to fast growth in the use of foils on sailing and power boats, both for racing and cruising. Foiling allows unprecedented speed and comfort, but it raises significant design challenges regarding control and safety. In the recent 2024 America's Cup, boat speeds over 50 knots have been reached.

The project aims to develop an in-depth understanding of the unsteady hydrodynamics of America's Cup hydrofoils, including issues related to cavitation and ventilation. It will be performed in partnership with world-leading yacht designers and professional sailors and potentially affiliated with an America Cup team.

There is no closing date for this position, which will remain open until filled.

Prof. Viola leads the Vortex Interaction Laboratory, VOILAb (https://voilab.eng.ed.ac.uk)

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Applications are welcomed from those who have secured their own funding through scholarships or sponsorships. No internal funds are available for this project.

The Javan cucumber (Alsomitra macrocarpa) is a vine that climbs the trees of tropical forests toward the canopy and sunlight. At great heights, it grows pods that contain hundreds of winged seeds. As the wind blows against the opening of the pods, the samaras are peeled away and released. Unlike many gliding seeds that use auto-rotation, the seed of the Javan cucumber vine exhibits a stable gliding flight with its paper-thin wings. The seed's design is efficient enough to achieve a slower rate of descent compared to that of rotating winged seeds. This aerodynamic advantage allows the seed to be easily carried by the wind several hundred metres. It is possible for the seeds to glide up to hundreds of meters, ensuring that they spread far from each other as well as the parent pod. This wide dispersal prevents the seeds from competing for resources once they fall to the ground and begin growing.

The membranous wings of the Alsomitra macrocarpa fruit are very thin, varying from a few micron to some tens of microns. The wing has a swept and tapered planform, resembling that of a flying wing (see figure). Such a wing is one of the most efficient fixed-wing aircraft designs, since the entire body provides lift; however, without electronic stablisers, “flying wing” aircraft are difficult to control. The Alsomitra macrocarpa fruit, however, has overcome this design weakness by having a center of gravity located close to (but in front of) the aerodynamic center of the wing due to the swept planform. At the same time, elastic deformation of the wing provides a twisted washout and dihedral, which helps it fly in a straight path and prevents “spiral instability” [1].

This project aims to reveal the origin of this fruit's incredible flight capacity. We will achieve this through numerical modelling of the wing using computational fluid dynamics, and flow visualisation and particle image velocimetry techniques with real seeds and scaled-up models of the seeds.

There is no closing date for this position, which will remain open until filled.

[1] Azuma, A., 2012. The biokinetics of flying and swimming. Springer Science & Business Media.

Prof. Viola leads the Vortex Interaction Laboratory, VOILAb (https://voilab.eng.ed.ac.uk)

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Applications are welcomed from those who have secured their own funding through scholarships or sponsorships. No internal funds are available for this project.

The proposed project aims to investigate the fluid dynamics of yacht sails. Sails have unique flow features, which allow the generation of very high lift and high lift/drag ratio compared to wings and blades commonly used in other fields such as aeronautics and turbomachinery. The project aims to understand the underlying mechanisms of these flow features in order to further enhance the performance of sails and, importantly, to allow the cross-fertilisation of ideas in research fields where there is a need for fluid dynamic efficiency.

The flow field around sails has several uncommon characteristics. The sharp leading edge leads to laminar separation, followed by a laminar-to-turbulent transition and then turbulent reattachment, forming a leading edge vortex (LEV). LEVs are known on flat plates with a sharp leading edge and on delta wings, while on rounded-nose foils used for low-pressure turbines, a similar feature known as the laminar separation bubble (LSB) occurs.

In the present project, it is proposed to test large-scale flexible sails in a wind tunnel to measure forces and the flying shape of sails and then to build a rigid small-scale model to be tested in a water tunnel to perform flow measurements with particle image velocimetry. Experimental measurements will be complemented with computational fluid dynamics simulations to test a wide range of conditions, which are tested with difficulty experimentally.

There is no closing date for this position, which will remain open until filled.

Prof. Viola leads the Vortex Interaction Laboratory, VOILAb (https://voilab.eng.ed.ac.uk)

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Applications are welcomed from those who have secured their own funding through scholarships or sponsorships. No internal funds are available for this project.

PhD in Electrical Engineering, Pontificia Universidad Catolica de Chile and University of Edinburgh, 2023.

Título de Ingeniero Civil Electricista (Electrical Engineer), Pontificia Universidad Catolica de Chile, 2016.

• Member of the Institute of Electrical and Electronic Engineers (IEEE)
• Member of the Institution of Engineering and Technology (IET)
• Next Generation Network (NGN) Member of CIGRE