Senior Researcher or Researcher in Applied Mathematical Signals Processing

at  The National Oceanography Centre

Senior Researcher or Researcher in Applied Mathematical Signals Processing
National Oceanography Centre, Southampton
Permanent Appointment
Full time (37 hours per week)
We are happy to consider applicants at Band 5 or Band 6, depending on experience:
Band 5: £50,017 - £55,016 / Band 6: £40,444 - £44,366
Who are we?
We are the National Oceanography Centre (NOC) - the UK’s leading institution for integrated coastal and deep ocean research. Through our ground-breaking research, collaboration, and game-changing innovation we work to gain a deeper understanding of our ocean, helping every living thing on our planet flourish.
We are made up of a dynamic and vibrant community focused on solving challenging long-term marine science problems, underpinning international and UK public policy, business and societal outcomes.
The ocean has the potential to provide the solutions to so many of the social, economic and environmental challenges we face worldwide. To truly harness the value of the ocean, we put ocean research, science and discovery at the heart of our culture.
Join us in shaping the future of oceanographic research and contribute your unique perspective to our organisation.
Preamble to the role:
NOC continues to develop novel (unprecedented dense space-time) environmental observational capabilities and bespoke development of the corresponding signals processing and analytics. These advances in observational capabilities of our natural environment (e.g., marine) have resulted in data-deluge. A single passive marine environmental observation source, e.g., seafloor cable of energy and/or telecommunications, could easily result in data streams of the order of ~ 10 GiB/s. Such data-fluxes pose significant data management challenges, e.g., in coherent processing and analytics over the in-field life (~ 30 years) of a single cable. The prospect of upscaling this low-cost sustainable wide-area dense space-time marine-environment observational potential, through use of the entire seafloor cabled infrastructure on the planet, more acutely will face-off with this data-management predicament. When operating with agnosticism to environment settings (e.g., water depth, temperature, flow velocity, pressure, seafloor characteristics etc), the problem seems to further escalate the need for a robust solution.
We’ve taken several key steps towards tackling the scale of this problem. Some of which comprised defining the global problem. General solutions to such problems can then be obtained using myriads of constructs from applied mathematical signals processing and enable adequate coverage to the emerging opportunities. Few examples of such problem definitions (PD) and potential opportunities (PO) may comprise (though not limited to):
PD1: High dimensional data processing & analytics; PO1: Obtain deeper understanding of the properties of large random or nonlinear non-stationary systems (e.g., submarine dynamics, albeit working closely with domain experts at the NOC). It will lend itself to improving our understanding of the marine environment its impact to climate and changes thereof. It will also address the growing need for tackling of the complexity of the sensor network requirements for adequate spatio-temporal sampling coverage of the marine environment.
PD2: Strategies for analysing interactions between events of competing interest; PO2: informing reprocessing of the data from the sensor-nodes for optimal resource allocation and designing mechanisms for achieving related specific objectives, e.g., to support adequate on-the-fly analytics on high-throughput data. As an extension will enable real-time vectoring on events of choice/interest, by operating at different spatio-temporal focal points, within the data.
Emerging opportunities comprising observations on other planets and/or their moons with marine-like settings, will hugely benefit from the observational preparedness acquired as part of this work-program.
Summary of work
In this position candidates must appreciate the PDs and POs (a few illustrated above). As a B6, they should work to address these by exploiting the diversity of applied mathematical signals processing (AMSP) tools, on the bigdata streams, e.g., obtained from submarine cable(s), in combination with others from more traditional marine observational platforms (satellite, mooring based instruments etc.) and domain specialist scientists at the NOC.
We are looking for original thinkers capable of independently carrying out AMSP routines in coherence with the identified requirements, writing papers and proposals with the PI, albeit with view to graduating to more independent roles.
An individual at B5 will be expected to bring to bear more advanced AMSP tools, at identifying and then addressing the evolving PD and PO space within this program (dense space-time environmental observations) of work. Advanced ASMP tools are outlined in the following section.
About you
We are looking for someone with a PhD in applied mathematical sciences, which could comprise, for example (though not limited to) applied physics/mathematics, electrical/electronic/audio/mechanical/aeronautical engineering or telecommunications, geophysics etc.
You must have knowledge in the use of fundamental and applied mathematical skills for signals processing (e.g., matrix algebra, filter design, linear & nonlinear transforms, time-frequency analysis with view to nonlinear-nonstationary signals analysis, statistical signal processing etc.). You should also be proficient in translation of your applied mathematical skills to enable automation/efficient programming routines in MATLAB/Python. Experience substantiating the above requirements, will be preferred.
At band 5, applicants must have knowledge of using advanced AMSP tools, e.g., Random Matrix Theory, Game Theory, complex transforms etc. on real data.
Why NOC?

We offer a generous set of benefits, including:

• 30 days contractual annual leave, plus 3.5 extra closure days and bank holidays
• a 10% employer contribution pension scheme
• access to our Employee Assistance Programme, offering free and anonymous support on mental, physical, emotional, health and financial issues
• access to a flexible benefits portal offering online discounts, cashback and eGift cards
• a Cycle2Work scheme allowing employees to acquire bikes and accessories
• a great working environment with a number of social events, including summer and Christmas celebrations

Location
This position will be based in Southampton. The centre is well connected by public transport and has ample cycle parking in addition to free onsite car-parking with over 40 EV charging points.
We can support visa applications where required. We may be able to offer financial support for applicants who will need to relocate for this position.
Submitting an application
Please click ‘Apply for this job’ and submit an up-to-date CV and cover letter. If you are unable to apply online, please contact the NOC recruitment team at careers@noc.ac.uk / 07955 851648.
Before submitting your application please ensure you have reviewed the attached job description and person specification.
We are committed to fostering diversity and inclusion in our workplace. We actively encourage qualified candidates from all backgrounds to apply for this position, as we strive to create a supportive and equitable environment where all voices are valued and heard.
Those seeking employment at NOC are considered solely on their qualifications, skills and experience, without regard to gender, gender identity, age, race, religion, disability, sex, sexual orientation, relationship status, family status (including pregnancy / maternity leave) or any other protected characteristic.
There is a guaranteed interview scheme for suitable candidates with a disability. The NOC is an Investors in People organisation.
Date advert posted: 26/06/2024
Closing date: 24/07/202

Please refer the Job description for details