PhD studentship: Luminescent nanostructures for biosensing

This project targets the development of nanostructured materials to be used in sensing technologies. Special attention will be given to luminescent materials and their non-linear effects, such as upconversion, in order to create new transducers.

For this, we are looking for a creative and highly motivated student to work in the field of luminescent nanomaterials and sensing technologies. Studies in Physics, Materials Engineering, Chemistry, or related, are desired. The student is expected to work effectively as a part of a team, both in the institution itself and with external partners. A good academic record and excellent organisational and lab skills are required.

During the project, new nanostructures for sensing will be produced. For this, the student will be introduced to nanofabrication via chemical and physical routes. Luminescent phenomena will be used as a sensing principle, and optical characterisation of the materials as well as of the completed devices will be required. The student will be expected to collaborate closely with the partners developing other parts of the sensors.

All applicants must have or expect to have an MChem, MPhys, MSci, MEng or equivalent degree by autumn 2017.  Good academic record and excellent organisational and lab skills are required. Candidates are required to be UK or EU nationals.

Selection will be based on academic performance, matching to the project and research potential, and all short-listed applicants will be interviewed (in person or via Skype).  The student will be awarded an annual stipend for 3 years, approx. £14,553 (tax free) the first year, which will be incremented each following year, and full payment of fees in order to complete the PhD thesis.

Deadline for applications: Tuesday 11th July 2017.  The start date is flexible, although September/October is recommended.

If you wish to discuss any details of the project informally, please contact Dr. Jose Marques-Hueso, Email: J.Marques@hw.ac.uk

All applications should be made online by using the electronic system of Heriot-Watt University:

https://www.hw.ac.uk/study/apply/uk/postgraduate.htm

Please attach a complete CV and motivations letter.

Multiple Vehicles Maritime Autonomy for Oceanography

Monitoring oceanographic phenomena, be they physical, chemical or biological requires sample data, taken at the right place, time and frequency to detect, qualify and model them. Currently, this is typically done from ships, moored or drifting platforms with limited embedded intelligence and no ability to modify their trajectories to adapt their sampling strategy. Gliders and autonomous surface and underwater vehicles have recently been introduced and have the ability to perform 3 dimensional sampling whilst controlling their location precisely. However, they are currently using pre-planned missions and do not adapt to the sensors measurements. They also do not collaborate as a team to tackle a joint mission optimally. As these platforms mature and become a commodity, they have the potential to become a powerful and adaptable sensor network. What is required is the autonomy framework to manage the collaboration of the platforms together with the signal processing theory to understand the core issues of sparse sampling and reconstruction of the underlying phenomenon that network is observing, whilst taking into account the communications limitation of the underwater domain.

We propose to develop an autonomy architecture which tackles this generic problem (mobile sensor networks sampling theory) and apply it to one (or more) oceanographic problems. The target applications will involve the deployment of surface and underwater vehicles, equipped with relevant sensors (chemical, biological) whose collective target is to detect and monitor a specific scientific event by adapting the sampling strategy of the network to provide the best possible model of the observed event. We expect the architecture to be fully decentralized (each platforms takes its own decision based on information provided by its neighbours) and its adaptive behaviours to be driven by a mixture of offline modeling of the phenomenon and on-line adaptation to live sensor data. The system will be developed in collaboration with SeeByte ltd who have been involved in an SBRI project with NOC on Adaptive Autonomous Ocean Sampling Networks and are interested in sponsoring a Case studentship to continue this line of research. The validation would be performed in Heriot-Watt university on the Oceans Systems Lab assets in the initial stages but would eventually be tested on a real scientific issue using the MARS fleet.

Two scientific applications are envisaged to guide the development: open ocean deep convection and spring phytoplankton blooms.  (1) Open ocean deep convection is a sporadic process where wintertime atmospheric cooling can make surface waters sufficiently dense to mix deeply (to 1000m or more).  A field of convecting plumes is expected to be in a localized region of water---O(100km) across---surrounded by stratified water.  The convective region is dotted with narrow mixing plumes (O(100m) across) where.  A decentralized sampling system would enable near-real time mapping of the convective patch, where underwater vehicles could identify and characterize the boundary between convecting and stratified water, and higher resolution sampling within mixing plumes.  (2) Phytoplankton blooms occur in the springtime, and are characterized by “patchy” areas of high fluorescence or production, interspersed with areas of relatively weak production.  An adaptive sampling network could be applied to find, and then characterize, the spatial scales of phytoplankton production at high resolution.  In both cases (1) and (2), the underwater sampling can be enhanced by surface measurements including meteorological data (in the case of convection) and irradiance (in the case of production).

The NEXUSS CDT provides state-of-the-art, highly experiential training in the application and development of cutting-edge Smart and Autonomous Observing Systems for the environmental sciences, alongside comprehensive personal and professional development. There will be extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial / government / policy partners. The student will be registered at Heriot-Watt University, and will share time between Heriot-Watt and SeeByte.

The student will work in a multi-disciplinary team of engineers and scientists. The student will get exposure to the commercial world through its links and time spent at SeeByte ltd. He/She will also get a strong understanding of the embedded software required to smarten the current generation of autonomous systems and will be able to adapt them to new problems in the future.

For informal enquiries please contact Prof Yvan Petillot, Head of Sensors, Signals & Systems at Heriot-Watt University.

EPS Funded PhD Scholarship on Robotics

The School of Engineering and Physical Sciences (EPS) at Heriot-Watt University is offering full fees and stipend for 3 years fully-funded PhD studentship to UK/EU applicants on physical human-robot interaction and assistive robotics with medical application. Heriot-Watt University is recognised as one of the leading UK research institutes in general engineering as per the Research Excellence Framework (REF) results of 2014 (ranked 1st). The student will be supervised by Dr Mustafa Suphi Erden of the Institute of Sensors, Signals, and Systems (ISSS) based at EPS at Heriot-Watt University.

This PhD project is an integral part of a wider research on developing robotic trainers and assistants for minimally invasive surgery (MIS) operations in the medical domain. The research includes capturing surgeon skills, developing physically interactive robotic trainers for haptic and manipulation skills, developing physically interactive robotic assistants for co-manipulation, identifying surgeon skill level through electromyography (EMG) registering from arm muscles and through near-infrared spectroscopy (NIRS) monitoring of cortical brain activity. The PhD student will work in close cooperation with other PhDs and post-doctoral researchers.

Specific to this position are,

1) Taking part in skill capturing for MIS through kinematics analysis,

2) Taking part in robotic measurement of surgeon hand-impedance and their analysis,

3) NIRS cortical brain monitoring for MIS skill level identification,

4) Developing robotic trainer for MIS with feedback from NIRS monitoring,

5) Developing robotic assistant for MIS with feedback from NIRS monitoring,

6) Taking part in integration of the robotic trainer and assistant with feedback from EMG registering.

The project requires knowledge and experience with robotic manipulators and machine learning techniques. Knowledge and experience with medical robotics and medical applications is desirable.

Physical Human-Robot Interaction and Assistive Robotics at ISSS

The physical human-robot interaction and assistive robotics research group aims to develop both robotic assistance and robotic training technologies for industrial and medical applications. Their research focuses on (1) understanding human behavior and human factors in manipulation tasks within the actual task environment, (2) design, control, and implementation of robotic assistants to help humans in these tasks by using knowledge of human behaviour and human factors, and (3) design, control, and implementation of robotic trainers to ameliorate and speed up training of novice subjects. One of the streams of their research is fine manipulation tasks requiring professional skills, such as manual welding in industry and minimally invasive surgery in medicine.

How to Apply

Applications should be made online. Applications will be accepted up to the point of recruiting a suitable candidate. Enquires about the research project should be made to Dr Mustafa Suphi Erden.

Besides the formal forms and papers for the online application, the following are required:

1) A motivation letter (at most two pages) stating your background in relation to the project and why you are interested in the position,

2) A transcript of bachelor and master program grades,

3) Any conference or journal publications and Master thesis or dissertation you have written.

James Watt Scholarships

As part of an ambitious expansion programme to intensify further our world-leading research programmes, Heriot-Watt University is offering a fourth round of James Watt Scholarships in the School of Engineering & Physical Sciences.

The James Watt scholarships will provide full fees and stipend for 3 years from Autumn 2017.

James Watt Scholarship projects leading to a PhD in Electrical Engineering

Heriot-Watt University has now created additional Doctoral Training Partnerships and James Watt Scholarships in the School of Engineering & Physical Sciences for 2017. The James Watt scholarships will provide full fees and stipend for 3 years from Autumn 2017, whilst the DTPs provide full fees and stipend for 3.5 years.  These scholarships are described below.

Requirements

All applicants must have or expect to have a 1st class MChem, MPhys, MSci, MEng or equivalent degree by Autumn 2017.  Selection will be based on academic excellence and research potential, and all short-listed applicants will be interviewed (in person or by Skype).  DTP’s are only open to UK/EU applicants.

Level of Award

For James Watt Scholarship students, the annual stipend will be £15k and full fees will be paid, for 3 years, whilst for DTP Scholarship students, the annual stipend will be £14,296 and full fees will be paid, for 3.5 years

JWS2017/20 : Manufacture of a bio-reactor for the production of artificial spider silk

Supervisor: Prof. M. Desmulliez, email: m.desmulliez@hw.ac.uk

JWS2017/21 : Microwave and antenna technology for satellite communications

Supervisor: Prof. G. Goussetis, email: g.goussetis@hw.ac.uk

JWS2017/22 : Acoustic Sensor Networks for subsea extreme environments

Supervisor: Prof. Y. Petillot, email: y.r.petillot@hw.ac.uk

JWS2017/23 : Bio-inspired Additive Manufacturing for 3D printed multimaterial integration

Supervisor: Dr. J. Marques-Hueso, email: J.Marques@hw.ac.uk

JWS2017/25: Advanced Signal Processing for Compact Deployments of Massive-MIMO Wireless Systems

Supervisor: Dr. M. Sellathurai, email: M.Sellathurai@hw.ac.uk

How to apply for James Watt Scholarship

For more information about how to apply, please apply online.

BASP Group Positions

Research associate and PhD positions are available with the Biomedical and Astronomical Signal Processing (BASP) group. Please refer to the BASP webpage.

Vacancies: Research Fellow/Post-Doc Positions available, please contact M.Sellathurai@hw.ac.uk if you are interested in PhD studentships and postdoctoral fellowships with the group in the area of signal processing for communications research.