Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
of publications in high-impact Q1 journals applying computational methods to materials science. Advanced proficiency in Python, ML libraries (PyTorch/Scikit-learn), MLOps, Docker, and computational materials
-
Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
Python or Java script familiarity with the following tools will be highly appreciated: Monfgo DB , React an dreact workflow, Google API´s, Pytorch Professional Experience: Programing in PYTHON/C languages
-
implement Python scripts for the automated control of electron microscopes; design and execute automated experiments, including real-time feedback loops between acquisition and data analysis; maintain
-
maintenance of the FAIR Knowledge Base, ensuring all experimental and simulation data is searchable and reusable. Professional-grade Python skills with a focus on maintenance. You will be responsible
-
navigating cloud-based research platforms to ensure data is not just stored, but is searchable, well-documented, and preserved for the long term. Knowledge of modern programming languages (e.g., Python, SQL
-
- Knowledge of programming (Fortran, Python) - Previous experience with SIESTA will be a plus but it is not essential. - Previous experience with user-level High Performance Computing will be a plus but it is
-
: Education: PhD in Biomedical, Neuroengineering, Electronic or Electrical Engineering, Physics, Bioinformatics or related engineering fields · Advanced Python / MATLAB programming skills. · Electrophysiology
-
or similar. Knowledge and Professional Experience: Programming Languages: Solid knowledge in at least one of the following environments (and willingness to learn others): Python (Django), PHP (Laravel