PhD - Multimodal Generative AI for Materials Design — EPFL
- Location
- Lausanne
- Contract
- full-time
- Posted
- 93 days ago
Role overview
Mission
EPFL is one of the most dynamic university campuses in Europe, ranks among the top 20 universities worldwide and offers an exceptional working environment with very competitive salaries.
- Mission
- EPFL is one of the most dynamic university campuses in Europe, ranks among the top 20 universities worldwide and offers an exceptional working environment with very competitive salaries.
- Main duties and responsibilities As a PhD Student, you will be expected to:
- Have full responsibility for your own dissertation
Main responsibilities
- Main duties and responsibilities As a PhD Student, you will be expected to:
- Have full responsibility for your own dissertation
- Research in close collaboration with academic partners; Experiment design and execution ;
- Analyze and interpret experimental results;
- Write scientific articles for publication in peer-reviewed journals;
- Present at international conferences. Supervise student projects We offer
- 4 years to complete your PhD with a competitive remuneration
- A world-class research and training environment with access to state-of-the-art research facilities; A multi-cultural and stimulating work environment;
- International collaboration and research internships at other institutions in Belgium and France;
- Term of employment: 1-year fixed-term contract (CDD), renewable for 4 years. Informations
Application process
- The LTS2 Lab https://lts2.epfl.ch offers a highly motivating, interdisciplinary scientific environment with many opportunities to interact between different projects and researchers, and has an excellent network of collaborative research projects with applications ranging from biology to neuroscience.
- The objective of this project is to develop groundbreaking generative AI methodologies for the design of novel materials.
- This is part of a large ERC Synergy project involving de novo simulations, automated experimental platforms driven by AI models.
- It offers extraordinary opportunites to collaborate with materials scientists on a quest to set-up a new blueprint for materials discovery, from computational approaches to actual synthesis and characterization. Profile
- We are looking for 2 PhD students who will contribute novel multimodal generative AI architectures, latent diffusion processes, and reinforcement learning approaches.
- Interestingly, the proposed model will interface with an automated platform performing experimental materials synthesis and incorporate data from experimental characterization and simulations.
- We are looking for PhD candidates with a strong analytical background, and an outstanding MSc degree in Engineering, Computer Science, Physics, Applied Mathematics, or a related field.
- You should be proficient in or willing to learn generative deep learning – in particular based on latent diffusion, multimodal approaches, statistics and learning theory.
Contacts
- information
- At least 2 references willing to write a recommendation letter.
- For more information, please contact: [email protected]
- Activity Rate : 100.00 Contract Type : PhD Student Reference : 2048
Additional details
- It offers extraordinary opportunites to collaborate with materials scientists on a quest to set-up a new blueprint for materials discovery, from computational approaches to actual synthesis and characterization. Main duties and responsibilities As a PhD Student, you will be expected to:
- Research in close collaboration with academic partners; Experiment design and execution ;
- Present at international conferences. Supervise student projects
- A world-class research and training environment with access to state-of-the-art research facilities; A multi-cultural and stimulating work environment;
- Term of employment: 1-year fixed-term contract (CDD), renewable for 4 years.
- Only applications submitted through the online platform are considered. Your application should contain: Contact information
- Activity Rate : 100.00 Contract Type : PhD Student
Notes and original content
- It offers extraordinary opportunites to collaborate with materials scientists on a quest to set-up a new blueprint for materials discovery, from computational approaches to actual synthesis and characterization.
- Main duties and responsibilities
- As a PhD Student, you will be expected to:
- Research in close collaboration with academic partners;
- Experiment design and execution ;
- Present at international conferences.
- Supervise student projects
- A world-class research and training environment with access to state-of-the-art research facilities;
- A multi-cultural and stimulating work environment;
- Informations
Questions about this listing
What salary does EPFL offer for this role?
EPFL lists CHF 60'500 - 91'500 gross per year for this position in Lausanne. This is the salary published in the original listing (or, when the employer omits a figure, a realistic estimate for the role and sector) — the calculator on this site converts it to your actual net take-home once cross-border tax and social contributions are applied.
Is this a full-time role, and what type of contract does EPFL offer?
This listing is a full-time position. The contract type shown here comes directly from the employer's original posting; always confirm exact hours, notice period and probation length with EPFL during the application process, since these details can vary by role even within the same contract category.
Do I need a cross-border work permit for a role in Vaud?
EU/EFTA residents living in the border zone of the country adjoining Canton Vaud can apply for a G permit; the Swiss employer files it with that canton's migration office after the contract is signed. Border-zone rules and processing times vary by neighbouring country and canton, so confirm the specifics with Vaud's cantonal migration office or with HR during the application.
How do I apply for this position at EPFL?
Use the "Apply now" button on this page — it links directly to EPFL's original listing at careers.epfl.ch, so your application goes straight to the employer's own applicant-tracking system. Frontaliere Ticino does not collect or forward applications itself.
