13 Postdoctoral Fellowship at Heriot-Watt University, Edinburgh, United Kingdom

The role will be based between the departments of Actuarial Mathematics and Statistics department and the Edinburgh Business School.  The Department of Actuarial Mathematics and Statistics is a vibrant and welcoming place. It is internationally renowned in actuarial science, with several high-quality degree programmes in actuarial science and actuarial management.  It is within the School of Mathematical and Computer Sciences, along with the Department of Mathematics and the Department of Computer Science. The School is a partner in the Maxwell Institute for Mathematical Sciences which brings together research activities at Heriot-Watt University and the University of Edinburgh. 

The Project Vision is to develop a coherent framework that enables humans and machines to work as a team by establishing and maintaining a single shared view of the world and each other’s intents through transparent interaction, robust to a highly dynamic and unpredictable maritime environment. We aim at removing workers from harsh and extreme environments to replaced them with teams of smart robots able to do the ‘dirty and dangerous jobs’, collaborating seamlessly as a team with each other and with human operators and experts on-shore. In this new world, remote data collection, fusion and interpretation become critical, together with the ability to generate actionable decisions from this data, sending remote robots to perform actions autonomously.

We are seeking motivated and enthusiastic people to work with us to assess the technical potential of several carbon dioxide removal technologies. Carbon dioxide removal is recognised as an important part of meeting climate targets, but the merits and drawbacks of many approaches remain poorly understood. Upon completion of these ambitious projects, the research team will have completed ground-breaking research on the performance assessment of several CDR approaches and provided the field with a framework for best practice that will form the standard for the field.

The projects are led by Prof. Wiaux and supported by a unique team of international partners: Prof. Pesquet from the Digital Vision Centre at Université Paris-Saclay (CentraleSupelec), Prof. Thiran from the EPFL Signal Processing Laboratories, Mr Jackson at the UoE Parallel Computing Centre (EPCC), Prof. Smirnov from the South African Radio Astronomy Observatory (SARAO), Dr Bouman and Prof. Hallinan from the California Institute of Technology (Caltech), Prof. Laing from the International Square Kilometre Array Organisation (SKAO), and Dr Neji from Siemens Healthineers UK.

We are seeking to appoint multiple Research Fellows with a passion for computational modelling and aspirations of an academic career. The positions will be aligned with advancing research in the McCabe and Cummings’ research groups at Heriot-Watt University and developing highly competitive candidates through the fellowship for academic careers. This will be done through focused professional and leadership development. Research in the McCabe group focuses on modelling self-assembly in biological systems and molecular theory to develop equations of state for a wide range of industry-inspired applications. In the Cummings group, the primary focus is on modelling capacitive energy storage devices. Jointly McCabe and Cummings conduct research on using machine learning methods to develop new materials for various applications and on software development for molecular modelling (i.e., the MoSDeF open-source software environment for automating molecular simulations: http://www.mosdef.org).

This project will address these knowledge gaps by undertaking a systematic review (SR) and meta-analysis to synthesize current empirical scientific evidence on the impacts of trawling on benthic carbon stores, sediment resuspension, bioturbation and physico- and chemical parameters that regulate carbon remineralization and storage across the ocean floor. The influence of factors such as gear penetration depth, disturbance frequency, ground type (biogenic, cohesive and permeable sediment), time of the year and natural disturbance will be examined on these relationships. These estimates and relationships will be used to inform ocean models of fishing impacts on carbon stores.

This research associate position is part of a large multidisciplinary research project on maximising CO₂ storage in complex carbonate rocks. The candidate will benefit from interactions with other team members with expertise in X-ray imaging, 3D image processing, in situ multiphase flow experiments at subsurface pressure and temperature conditions, pore-network modelling, direct numerical simulations and machine learning.

The Institute of Signals, Sensors and Systems (ISSS) is one of five Research Institutes forming the research infrastructure of the School of Engineering & Physical Sciences (EPS). With 30 academic members of staff spanning 10 nationalities and 4 fields of expertise, ISSS aims to offer the full portfolio of expertise in the fields of signal and image processing, novel manufacturing technologies, microsystems, microwave engineering, mobile communications systems and autonomous systems. Of particular interest to ISSS is the design, modelling, simulation, processing of information from and system integration of sensors. The Signal and Image Processing Laboratory (SIPLab) at Heriot-Watt specializes in the design of advanced data science techniques with applications ranging from robotics to imaging and communication, in a large variety of fields including defence, astronomy, art investigation, or medicine. Our research activities range from signal and image processing theory to application, and impact different areas of society. SIPLab is active in both traditional and emerging areas, and currently covers the following topics:

We are seeking a creative and motivated post-doctoral researcher to work as part of our international and multidisciplinary USorb-DAC (“Unlocking the scalable potential of sorbent-based DAC technologies”) team and with expertise to support our research activities in the project. The project’s aim is to discover adsorbents that can drastically reduce DAC’s energy intensity and cost so that DAC can scale rapidly and contribute to fighting climate change. By coupling basic science with engineering and environmental aspects, the team will develop an in-depth understanding of materials structure-property-performance relationships across different time scales and under relevant and realistic DAC operation conditions.  

Successful applicants for this Research Associate role will join the multidisciplinary, award-winning project TAS Node in Trust (https://trust.tas.ac.uk/). The role holder will make a significant contribution to the human-robot interaction research conducted on the project, including all elements of experimental work (e.g., data collection, analysis, paper writing), public engagement, and dissemination through publication. The post holder also will become a member of the School of Social Science’s Centre for Applied Behavioural Sciences (https://cabs.site.hw.ac.uk/).

The successful applicant will either hold a good first degree and a PhD (or near completion) in Business Management; Finance; Economics; Business Analytics; Energy or similar discipline, or will come with extensive and relevant industrial experience. In the latter case, we will offer a fee waiver for those who is willing to undertake a PhD research degree. Under both routes, the candidate should have capacity to work independently and conduct high quality research, familiar with tools and techniques for analysing complex systems, qualitative (interviews, surveys) and quantitative data analysis, with excellent written and oral communication and presentation skills, and the ability to work in a diverse team of academic and industrial partners.