Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
Process in the Interviews phase Project Title: Data-Driven Optimization of PtAg Hollow Nanocrystals Synthesis - Master's degree internship Group:Inorganic Nanoparticles Group, ICN2 Supervisor: Dr
-
performance. A key aspect of the PhD will be the systematic documentation and curation of experimental data in a FAIR-compliant materials database, including synthesis protocols, characterisation results, and
-
project around the development of AI models for predicting promising catalyst candidates to integrate molecular modelling techniques, experimental data bases and materials data bases together with novel AI
-
. Applicants are invited to propose a research project around the development of AI models for predicting promising catalyst candidates to integrate molecular modelling techniques, experimental data bases and
-
(S)TEM. Requirements: Education: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science. Knowledge: Deep expertise in electron microscopy, particularly STEM and FIB methods
-
. Generate structural and electronic descriptors to support the development and training of machine learning models for materials discovery. Contribute to the definition of FAIR data standards for the results
-
computer-based systems and the preparation of data for inclusion in lab books, presentations and publications. Maintain a hardcopy or electronic lab book · Work in compliance with relevant Health and Safety
-
: Education: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science. Knowledge: Deep expertise in electron microscopy, particularly STEM and FIB methods. Proven experience in
-
: The candidate will be involved in the design and development of the software and programming tools for the read-out and data management of the optical biosensors. The main tasks include: Phyton programming and
-
, sparsity, and symmetry. Data pipeline: Curate datasets from DFT calculations (and, where relevant, Wannier/TB extractions); implement preprocessing, splits, and rigorous validation. Metrics and validation