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Nikolas
- Rate R1774
- Response 1h

R1774/h
1st lesson free
- Maths
- Statistics
Postdoctoral Researcher | Advanced Statistical Modelling and Machine Learning for Engineering and Research Projects
- Maths
- Statistics
Lesson location
About Nikolas
I am a Postdoctoral Researcher with a PhD in Coastal Engineering, specialising in multivariate statistical modelling of extreme events and neural-network applications in ocean and offshore systems. I have worked in academic and applied research environments in both the UK and Europe, contributing to projects in offshore monitoring, renewable energy, and coastal risk assessment. My work integrates applied mathematics, statistical inference, time-series analysis, and machine learning within research and engineering contexts.
In parallel with my academic career, I have over 20 years of experience teaching mathematics, statistics, and data analysis at university level. I have supported students, researchers, and professionals from engineering, health-related disciplines, psychology, and quantitative social sciences, working with both theoretical and applied datasets. My objective in offering this support is to help students and researchers approach complex analytical problems with confidence, precision, and a solid theoretical foundation.
About the lesson
- Primary
- Secondary
- Matric/GCSE
- +9
levels :
Primary
Secondary
Matric/GCSE
AS Level
A Level
BTech
Adult education
Undergraduate
Masters
Diploma
Doctorate
MBA
- English
- Italian
- Greek
Languages in which the lesson is available :
English
Italian
Greek
Work begins with a clear definition of the research question, dataset structure, and methodological requirements. Analytical work typically includes areas such as hypothesis testing, ANOVA, regression, multivariate analysis, copula-based dependence modelling, ARMA-type and stochastic time-series models, clustering, and advanced neural-network architectures (ANN, DNN, TCN, LSTM, GRU, Bi-LSTM).
All analysis is implemented in R, Python, MATLAB, Stata, SPSS, or other environments as required, with emphasis on reproducible workflows, model validation, performance evaluation, and clear interpretation of results.
Engagement is delivered through structured methodological guidance, collaborative model development, code review and optimisation, or full implementation of an analytical pipeline, depending on project needs and client objectives.
Sessions typically last 60–90 minutes and are intended for researchers, and professionals working with complex research datasets, MSc and PhD students. The aim is to deliver robust, publication-ready analytical outcomes that can be confidently defended in academic or professional contexts.
Rates
Rate
- R1774
Package rates
- 5h: R8871
- 10h: R17742
online
- R1774/h
free lesson
The free first lesson with Nikolas allows you to get to know the tutor and discuss your needs and expectations.
- 45min
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