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PhD in Mathematics Topics: Neural Networks, Scientific-Machine Learning, Differential Equations
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Assessing your cultural and operational fit
Institute for Artificial Intelligence
Data Scientist
June 24, 2026 – Present
tutorialNN4DEs
April 29, 2026 – Present
IJCAI 2026 Tutorial "Neural Networks and Differential Equations: From Infinite Layers to Continuous Modelling"
View ProjecttemperatureModellingDataset
August 13, 2025 – October 10, 2025
We introduce a structured, high-resolution dataset of transient thermal simulations for a vertical axis of a machine tool test rig.
View ProjectPINNsTutorialMAGNET4Cardiac7T
April 3, 2025 – April 6, 2025
PINNsTutorialMAGNET4Cardiac7T — repository
View ProjectintegratingPriorKnowledgeNNs
October 31, 2024 – May 20, 2025
integratingPriorKnowledgeNNs — repository
View ProjectPriorKnowledgeNeuralODE
July 27, 2023 – September 7, 2023
PriorKnowledgeNeuralODE — repository
View Projecticnaam2022
July 27, 2022 – September 21, 2022
Code to replicate experiments of paper "The role of adaptive activation functions in Fractional Physics-Informed Neural Networks""
View ProjectHydropower-Optimization-Project
October 28, 2020 – August 22, 2022
Optimization project for a course evaluation. The goal is to maximize the power generated in a dam while keeping a minimum river flow for wildlife preservation. The algorithms used are fminsearch, patternsearch, PSwarm, evolutionary algorithm, ga (genetic algorithm) and gamultiobj.
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated on academic research in machine learning and differential equations, primarily using Python and Jupyter Notebook. While this demonstrates deep expertise in a niche area, the diversity of projects and technologies outside of this specific domain is limited. The single listed work experience as a 'Data Scientist' at an 'Institute for Artificial Intelligence' aligns with the target role, but the lack of detail on responsibilities makes it hard to fully assess cultural fit beyond a research-heavy environment. The candidate's experience level is listed as 0, which contradicts the ongoing 'Data Scientist' role, suggesting a potential mismatch in how experience is categorized or a very recent start to their professional career. This narrow focus might limit adaptability to broader industry data science roles that require a wider range of tools and business contexts.
Soft Skills & Operational Fit
The candidate's profile suggests a strong research and academic orientation, which aligns well with roles requiring deep analytical skills and problem-solving. However, without specific psychometric test results, it is difficult to assess work attitude, stress handling, and team collaboration. The project descriptions are concise, indicating a focus on technical output.