Clinical Scientist jobs in United Kingdom
London-based Catastrophe Risk Scientist
The Emerald Group
Researcher-Junior(JRFP) (Code:EU3543)
European Institute of Policy Research and Human Rights SIA
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Rosalind Franklin Institute
Electron Microscopy Research Associate: Ptychography
Rosalind Franklin Institute
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University of Edinburgh
Research Associate, Human-Centred Climate Resilience
University of Edinburgh
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13471- Research Associate
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Biomedical Scientist in Immunology | East Kent Hospitals University NHS Foundation Trust
East Kent Hospitals NHS Trust
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Blackpool Teaching Hospitals NHS Foundation Trust
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Senior Research Scientist - Battery Materials
Centre for Process Innovation
Risk Scientist – 29283
Job summary
A leading catastrophe science firm in London is seeking a motivated technical specialist to join their Catastrophe Research team. The role involves performing advanced model evaluations, engaging with the latest scientific research, and effectively presenting results to diverse audiences. The ideal candidate holds a PhD in a relevant field and is proficient in programming languages like Python and R. This position offers the opportunity to work at the forefront of catastrophe science in a collaborative environment.
Qualifications
- Strong academic record with a PhD and relevant research focus.
- Proficiency in programming languages for data analysis, including strong preference for machine learning application.
- Ability to present results effectively to various audiences.
Responsibilities
- Perform and document model evaluation for high-risk areas.
- Stay updated with scientific research and emerging technologies.
- Provide relevant model evaluation materials for reporting.
- Present findings to clients, brokers, and senior management.
- Represent the company at scientific and industry forums.
Skills
Education
Tools
Our client is seeking a motivated and strongly technical specialist to join their Catastrophe Research team. Their team is a small, specialised group of applied researchers with advanced expertise and domain knowledge in atmospheric sciences, hydrology and seismology. Joining their team means working at the forefront of catastrophe science, shaping how research is applied in the insurance industry.
- Location: London
- Type: Permanent
Key Responsibilities (including but not limited to):
- Performing and documenting model evaluation deep dives for areas of high peril materiality and abridged model evaluations for lower materiality regions
- Keeping abreast of the latest scientific research and emerging technologies to inform novel approaches to developing business view of risk
- Assisting the provision of relevant model evaluation materials for company reporting
- Presenting results regularly to a wide range of audiences including clients, brokers, senior management and investors
- Representing company at national and international scientific and industry forums
- A strong academic record, to degree level (2:1 or Higher or equivalent) and a higher degree (PhD) including a period of specific research with a focus in a risk sciences area such as meteorology, climatology, seismology, or hydrology
- Strong proficiency in programming languages for data analysis (e.g. Python, R, SQL) with a strong preference for candidates who have hands-on experience applying machine learning or Al techniques to real-world problems
- The ability to and interest in working collaboratively across different teams
- Comfort in presenting both internally to senior management and investors and externally to clients or at industry or academic conferences
- It would also be beneficial if you have a strong interest or knowledge of the key principles of commercial catastrophe models, climate models and the data and formats used in climate modelling
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.