Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, and multi-level data analysis Communicate and collaborate with a research team, including teachers and student assistants Engage in international opportunities for learning and development (i.e
-
AI agents themselves. The candidate will explore behavioural analysis techniques. Another research questions is related to the definition and application of a unified policy through both legacy IT
-
to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
-
sharing clinical data from neurodegenerative disease cohorts. You will be responsible for: Technically contribute and coordinate the development and implementation of data systems and analysis platforms
-
datasets such as the Luxembourg Parkinson’s Study and different prodromal cohorts for neurodegenerative diseases are ready for analysis. The doctoral researcher will: Conduct research that will compose a PhD
-
) Probability and Stochastic Analysis, (4) Discrete and Geometric Analysis, (5) Statistics and Data Science, and (6) Partial Differential Equations and Modelling. The Faculty of Science, Technology and Medicine
-
Organize and prepare content/analysis for project events, such as stakeholder meetings and policy briefs Network with researchers and stakeholders to support the development of the project Engage in outreach
-
into cross-seeding between microbiome-borne amyloidogenic proteins and human proteins implicated in neurodegenerative disea Your responsibilities: The doctoral candidate will perform computational analysis
-
), a pioneering European project funded by the Innovative Health Initiative (IHI). IDERHA is building a federated health data platform to enable seamless integration and analysis of diverse biomedical
-
on multiscale analysis of brain disorders with a focus on Parkinson’s and Alzheimer’s disease, and epilepsy by combining experimental and computational approaches. For a collaborative project within the Institute