- RGU Garthdee, AB10 7GJ
- £25,000.00 - £35,000.00 per year
- Contract Type:
- Fixed Term
- Position Type:
- Full Time
- 37 hours per week
This position has expired.
This is an exciting opportunity for an ambitious Data Scientist to fast-track their career development as a Knowledge Transfer Partnership (KTP) Associate, utilising skills in Data Science with a specific focus on Machine Learning, Time Series Analysis, Image Analysis and Machine Vision. The successful candidate will undertake a 24 month collaborative project between AISUS Offshore Ltd and Robert Gordon University (School of Computing). The post will be based at the company’s offices in Aberdeen, where the post holder will take a leading role in the design, development and evaluation of a set of intelligent tools and algorithms for remote inspection. The post holder will play a key role in creating an intelligent data-driven platform utilising images, ultrasonic scans and other data captured by bespoke remote inspection tools to provide Oil and Gas Operators worldwide with more accurate assessment of the offshore assets.
AISUS offer a suite of remote inspection and cleaning solutions, which have been designed to solve key industry challenges internally, and externally of a structure. The company has an in-house design team and can design, build, test and qualify tooling to meet any project requirement. It operates across four continents and has a diverse portfolio of expertise in asset integrity of topside and subsea assets.
As a KTP Associate you will receive extensive practical and formal training, gain marketable skills, broaden knowledge and expertise within an industrially relevant project, and be supported by both industrial and academic mentors. The KTP Associate will benefit from a tax free Personal Development Budget of £4,000.
Candidates must possess a postgraduate degree in Data Science, Machine Learning, Computing or a strongly related discipline. PhD in Data Science, Information Engineering, Machine Learning or similar field is highly desirable. The candidate should be self-motivated with an ability to work independently and to tight deadlines within a dynamic and small team environment. In addition, they must have strong programming skills as well as a genuine enthusiasm for applying advanced methods to a real-world problem. Strong knowledge and understanding of programming languages such as R, Python, or similar langue is essential. Experience in handling unstructured data is highly desirable. Team working and flexibility will be a key requirement.
Salary Range: £25,000 to £35,000
Position Type: Full Time, Fixed Term 24 months, with potential for further permanent employment within the company upon contract completion.
Informal enquires may be sent to Professor Eyad Elyan at email@example.com
RESONSIBLE TO: Whilst working on company premises report to and take direction from the Head of Technology. Whilst working at Robert Gordon University report to and take direction from Professor Eyad Elyan.
RESPONSIBLE FOR: No Supervisory Responsibility
PURPOSE OF POST:
Take a leading role in designing, implementing and evaluating an intelligent set of methods to allow remote monitoring and inspection of Oil and Gas facilities and installations.
Transfer knowledge of data science and state-of the art machine learning techniques to AISUS.
Develop technical and personal skills (verbal and written) to meet the requirements of increasing responsibility and experience level.
Deliver the project objectives as detailed in the KTP project proposal.
Undertake an in-depth literature review in the area of machine learning, image processing, time series and video analysis.
Explore, understand and critically evaluate existing technologies and practices in use at the company.
Take a leading role in developing and evaluating the intelligent models for remote inspection.
Maintain an up-to-date project plan and provide regular progress reports.
Deliver presentations to immediate project team members and technical experts.
Any other duties that may be reasonable, assigned by the Academic Supervisor/ Company Supervisor.
Qualifications and Professional Membership
Candidates must possess a postgraduate degree in Data Science, Computing or a strongly related discipline.
Knowledge and skills
Strong knowledge of machine learning, machine vision and the underlying theories.
Strong programming skills (i.e. R, Python, etc…) and scripting skills.
Knowledge of Deep Learning, Deep Sequence Models and Time Series Analysis is highly desirable.
Self-motivated with an ability to work independently and to tight deadlines within a dynamic and small team environment.
An ability to undertake independent research and development analysis.
Willingness and ability to learn quickly Skills
Good communication and report writing skills are essential.
Very good problem-solving skills.
Experience in Data science related discipline is essential. Recent graduates with strong technical skills as outlined above are welcome to apply.
Qualifications and Professional Membership
PhD in Data Science, Information Engineering or a similar field