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La Comisión Europea busca candidatos para realizar una tesis doctoral en el Instituto de Ciencia de Materiales de Madrid, con su enfoque en química computacional y técnicas de IA. Este proyecto revolucionará el campo de las redes moleculares bidimensionales y mejorará la síntesis y caracterización de materiales orgánicos a nivel nano.
Organisation/Company agencia estatal consejo superior de investigaciones cientificas Department Instituto de Ciencia de materiales de Madrid Research Field Physics » Computational physics Chemistry » Computational chemistry Engineering » Chemical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Spain Application Deadline 31 Jul 2025 - 14:00 (Europe/Brussels) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Sep 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number TEC-2024/TEC-459 Is the Job related to staff position within a Research Infrastructure? No
We are seeking candidates to start a PhD thesis at the Materials Science Institute of Madrid (ICMM), a research institute of the Spanish Research Council (CSIC), in the framework of the SYNMOLMAT-CM Project (TEC-2024/TEC-459), funded by the 2024 Technologies Program of the Comunidad de Madrid. The SYNMOLMAT-CM project aims to revolutionize the field of two-dimensional molecular networks and organic electronics by incorporating advanced theoretical models, quantum chemistry methods, and artificial intelligence (AI) techniques. This approach will enhance the synthesis, characterization, and understanding of organic materials at the nanoscale, enabling the prediction of reactions inaccessible through conventional chemistry and optimizing the creation of functional materials for applications in magnetism, nanocatalysis, and optoelectronics.
Specific Tasks
The selected candidate will work on Objective 5 of the project SYNMOLMAT-CM: Development and Integration of Theoretical and AI Protocols, performing the following tasks:
1.- Application of Density Functional Theory (DFT) to predict electronic structures and properties of synthesized materials.
2.- Use of perturbation theory to analyze how small structural changes affect material properties.
3.- Implementation of advanced quantum chemistry methods (Coupled Cluster, MCSCF) to study excited states and charge transfer.
4.- Classical and QM/MM molecular dynamics simulations to study the structural evolution of complex materials.
5.- Development of neural network models, machine learning algorithms, and evolutionary algorithms for optimizing material synthesis and characterization.
6.- Application of AI in the visualization and analysis of STM and AFM images using convolutional neural networks and autoencoders.
7.- Use of reinforcement learning and Bayesian networks to optimize experimental processes and rationalize results.
Training Plan
The candidate will receive theoretical and practical training in:
1.- Computational simulation methods for materials, including DFT, perturbation theory, and molecular dynamics.
2.- AI techniques applied to materials science, such as neural networks, machine learning, and evolutionary algorithms.
3.- Advanced analysis of experimental data using computational tools.
4.- Scientific writing and presentation of results at international conferences.
5.- Collaboration in multidisciplinary projects with physicists, chemists, and computational scientists
E-mail ofertas_euraxess@icmm.csic.es
Research Field Chemistry » Computational chemistry Education Level Master Degree or equivalent
Research Field Physics » Computational physics Education Level Master Degree or equivalent
Research Field Engineering » Chemical engineering Education Level Master Degree or equivalent
Skills/Qualifications
Previous experience in programming and computational simulation (Python, Fortran, C++); Knowledge of machine learning techniques and data processing; Familiarity with computational chemistry software such as VASP, Quantum ESPRESSO, Gaussian, ORCA, LAMMPS; Skills in the analysis and visualization of scientific data; Experience working in multidisciplinary research environments.
Specific Requirements
Previous experience in computational quantum mechanics and first-principles methods will be valued; Teamwork skills and strong motivation for scientific research.
Languages ENGLISH Level Good
Research Field Chemistry » Computational chemistryEngineering » Chemical engineeringPhysics » Computational physics
Three-year predoctoral contract in a leading research group; Access to high-performance computing infrastructure and international collaborations; Opportunity for research stays in international centers; Training in transversal skills, including scientific writing, presentations, and project management; Participation in international conferences and workshops.
Eligibility criteria
Previous experience in programming and computational simulation (Python, Fortran, C++); Knowledge of machine learning techniques and data processing; Familiarity with computational chemistry software such as VASP, Quantum ESPRESSO, Gaussian, ORCA, LAMMPS; Skills in the analysis and visualization of scientific data; Experience working in multidisciplinary research environments.
Additional comments
ICMM-CSIC is deeply commited to preserving equal opportunities and inclusiveness, a philosophy that our group fully supports.
The applicants should send:
to this email address: ofertas_euraxess@icmm.csic.es . In the title (subject) of your email please write: PhD-2025-4. All materials should be in English and submitted in PDF format no later than 31th of July 2025, 14:00 h.
Number of offers available 1 Company/Institute Instituto de Ciencia de Materiales de Madrid (ICMM-CSIC) Country Spain State/Province Madrid City Madrid Postal Code 28049 Street c/Sor Juana Inés de la Cruz 3 Geofield