Statistical Modeller / Acoustician

Posted on Jun 11, 2021 in Job Opportunities in Acoustics

Closing date for applications: 28 June 2021

Vacancy: Statistical Modeller / Acoustician
Type: Full-time, permanent position
Salary: £34,000 – £40,000 depending on qualifications and experience
Location: Dunbar, East Lothian, Scotland, UK (potential for remote working)
Application deadline: 28th June 2021

Company
Ocean Science Consulting Limited (OSC) is a privately-owned and technology-focused marine-science company involved principally in the global supply of underwater noise and marine mammal monitoring, modelling, and risk mitigation services. OSC reinvests a significant proportion of profits into R&D, orientated primarily towards high-level research on the harbour porpoise (Phocoena phocoena) and other marine mammal species, Rigs-to-Reefs using ROV footage, underwater noise measurement and modelling, and improving marine mammal and environmental monitoring standards worldwide. OSC’s research has resulted in many peer-reviewed publications and a non-profit book entitled the Marine Mammal Observer and Passive Acoustic Monitoring Handbook.

Role
OSC seeks to expand its UK-based team. This is an opportunity for permanent employment as a PhD-qualified Statistical Modeller / Acoustician. The successful candidate will work across OSC’s scientific and commercial wings. The role will involve analysis of noise and echosounder data and statistical modelling of biological datasets for client reports and peer-reviewed publications.

This is a highly unusual position to contribute to scientific research in a commercial consultancy in an exciting and fast-paced organisation. This role offers opportunities for a self-motivated, enthusiastic individual to make a significant difference within a well-established and expanding company.

Job description can be found on: http://www.osc.co.uk/careers

Key duties
Analyse noise data collected during industrial operations (i.e. calculate transmission loss, source level, SPL, SEL, potential impacts to marine mammals/fish, etc.);
Acoustic propagation modelling (i.e. ray tracing, bellhop, normal modes, etc.)
Process echosounder data to remove turbulence and identify fish/school presence;
Conduct statistical analysis (e.g. GLM, GAM, PCA, HBM, INLA, time series analysis, distance sampling, abundance estimation, survey design, PCoD, etc.);
Contribute to client reports and peer-reviewed publications; and,
Oversee the peer-review process.

A successful candidate will have the following:

Required
A PhD or equivalent experience in a relevant scientific discipline (marine biology/marine ecology/acoustics/statistics/mathematics/oceanography, etc.);
Those without a PhD (or who are still a student) may apply; however, would be placed on a lower salary, and may only work part time if still a student;
Strong statistical analysis background ideally in R;
Previous experience with noise and echosounder data analysis, or the ability and motivation to learn this quickly;
Excellent spoken and written English;
A genuine interest in marine mammals and/or benthic ecology;
Ability to collaborate within a team setting to produce high-calibre publications and reports; and,
Must be legally allowed to work in the UK prior to employment (we cannot assist with visas).

Desirable
A minimum of two, first author, ecological-modelling related peer-reviewed papers;
Experience sourcing and processing oceanographic datasets (synoptic satellite-derived or modelled data, etc.) and handling data of various types including: netCDF, csv, txt, etc.; and,
Machine learning and image processing (of ROV imagery).

Supervisors
The successful candidate will be working under the supervision of Dr Victoria Todd (Dunbar office) and Dr Laura Williamson (Thurso office).

Interested candidates should send a CV and cover letter to: admin@osc.co.uk. This address can also be used for informal enquiries.

Applications will be reviewed after the closing date, and successful candidates will be invited to an interview via Microsoft Teams. An interview task will be provided comprising both written and practical components.

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