Vacancy: Statistical Modeller
Type: Full-time, permanent position
Salary: £34,000 – £40,500 depending on qualifications and experience
Location: Dunbar, East Lothian, Scotland, UK
Application deadline: 31st August 2020
The successful candidate will be working under the supervision of Dr Victoria Todd (Dunbar office) and Dr Laura Williamson (Thurso office).
There is increasing tendency to assess the physical habitat of cetaceans by examining their spatial distribution and fine-scale behavioural responses in relation to abiotic (synoptic oceanographic) parameters. Determination of these relationships can, on the large scale, enhance precision of density and abundance estimates, and on smaller scales (e.g. daily acoustic detections), disentangle effects of oceanographic variables from anthropogenic influences, such as potential effects of seismic exploration, drilling, installation of renewable energy structures (e.g. windfarms), defence activities, etc. Such analyses improve the way we manage and design conservation strategies for these species. Moreover, knowledge of a species’ habitat can help us predict where animals are likely to be, potentially decreasing impacts when undertaking anthropogenic activities.
Ocean Science Consulting Limited (OSC) is a privately-owned technology-focused marine-science company involved principally in the global supply of underwater noise and marine mammal monitoring, and risk mitigation services. OSC reinvests >80% of profits into Research & Development (R&D), orientated primarily towards high-level research on the harbour porpoise (Phocoena phocoena) and other marine mammal species, Rigs-to-Reefs using Remotely Operated Vehicle (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 (www.osc.co.uk/publications-and-press-covers) and a non-profit book entitled the Marine Mammal Observer and Passive Acoustic Monitoring Handbook (http://www.pelagicpublishing.com/the-marine-mammal-observer-and-passive-acoustic-monitoring-handbook.html).
OSC seeks to expand its UK-based team. This is a rare opportunity for permanent employment as a PhD-qualified Statistical Modeller. The commercial post doc role involves working primarily in OSC’s R&D wing, although suitable candidates may also be considered for a combination of consultancy/commercial duties. The role will firstly involve assimilation of oceanographical/biological productivity/bathymetric data, followed by untangling relationships between these data and marine mammal detections. The candidate will ideally have extensive knowledge of the variety of online-data inventories and data-holding centres from which data can be sourced (e.g. Copernicus, NOAA), and experience sourcing, downloading, handling, and analysing these data (e.g. ocean colour, Sea Surface Temperature (SST), Chlorophyll-a, etc.). These sources provide the main environmental variables with which marine mammal detections (echolocation-click detections using C-PODs, Marine Mammal Observer (MMO), and Passive Acoustic Monitoring (PAM) detections) will be investigated by way of temporo-spatial analytical/modelling techniques such as GAMs/GLMs.
It is anticipated that over the course of the first year, the candidate will bring to completion ca. five manuscripts for submission to peer-reviewed journals. Applicants must therefore be able to source, consolidate, analyse, interpret, and present these data in the form of high-level, peer-reviewed papers, that must be brought to completion on commercial and not academic timescales (i.e. weeks, not months), with minimal supervision from line managers (i.e. autonomous). This is a highly unusual position for academic research in a commercial consultancy; however, consultancy is not academia, and the work environment is extremely fast paced. The candidate may also be presented with urgent commercial requests as these arise and must therefore be able to switch from one project to another. Prioritisation is of high importance.
Job description can be found on: https://www.osc.co.uk/careers/vacancies
- Conduct statistical analysis of pre-existing datasets;
- Write manuscripts for submission to peer-reviewed journals;
- Oversee the peer-review process; and,
- Support colleagues with analysis of commercial datasets as and when required.
A successful candidate will have the following:
- A completed PhD in a relevant scientific discipline (statistics/oceanography/marine biology/marine ecology, etc.);
- The position requires a PhD; however, students may apply, but be aware that starting salary will be £27,000-30,000 (depending on qualifications and experience until the PhD is completed), and the position would be part time until the PhD was completed;
- Strong statistical analysis background ideally in R (e.g. GLM, GAM, PCA, HBM, INLA, time series analysis, distance sampling, abundance estimation, survey design, PCoD, etc.);
- A minimum of two, first author, ecological-modelling related peer-reviewed scientific papers in a top journal (i.e. not a proceedings paper);
- Experience sourcing and processing oceanographic datasets (synoptic satellite-derived or modelled data, etc.) and handling data of various types including: netCDF, csv, txt, etc.;
- Excellent spoken and written English (to peer-reviewed, non-copy-edited level);
- A genuine interest in marine mammals and benthic ecology, and an understanding of the physical parameters of the ocean which affect them;
- 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).
- Machine learning and image processing (of ROV imagery);
- Experience making publication-quality maps in QGIS; and,
- Experience with referencing software (e.g. EndNote).
Interested candidates should send a CV and cover letter to: email@example.com. 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 in early September (via Microsoft Teams). An interview task will be provided comprising both written and practical components.
OSC Recruitment Team