Postdoc (2 2-year appointments) Scientific Foundation Models for Materials (AIHPC)

Introduction

Are you excited about using large-scale AI to accelerate scientific discovery Join a Horizon Europe project developing next-generationscientific foundation modelsthat combine knowledge graphs multi-modal data and GPU-accelerated machine learning for materials science.

Job Description

We are seekingtwo highly motivated postdoctoral researchersto join the Horizon Europe projectSIMU-LINGUA a major European initiative developingscientific foundation models (SciFMs)for materials science.

SciFMs are emerging as a powerful paradigm for scientific discovery. SIMU-LINGUA addresses key challenges indata integration model design and large-scale trainingby combiningmulti-modal scientific data knowledge graphs physics-aware machine learning and GPU/HPC computingto developtransparent and trustworthy AI for science.

At Eindhoven University of Technology (TU/e) you will contribute to the projects core technical components:

• scientific data orchestration and knowledge graphs
• architecture and large-scale training of scientific foundation models

You will collaborate with researchers acrossmachine learning scientific computing materials science and data engineering and work with leading academic and industrial partners across Europe. The project will developmaterials ontologies training-ready datasets multi-modal knowledge graphs and large-scale SciFM models together with tools fortraining diagnostics and model observability. The firstpre-trained SciFM modelswill be released as part of the project. You will havesignificant scientific ownership contribute to publications and open-source software and help shape emerging methodologies forscientific AI and foundation models. Applicants should indicate aprimary research track although collaboration between tracks is expected.

Track A Scientific Data & Knowledge Graphs
You will developscalable scientific data infrastructuresenabling large-scale model training includingmaterials ontologies data ingestion and curation pipelines multi-modal knowledge graphs and training-ready datasets with robust provenance and validation.

Track B GPU-Accelerated Scientific Foundation Models
You will design and trainlarge-scale multi-modal foundation models includingSciFM architectures coupled to knowledge graphs GPU-accelerated PyTorch training pipelines distributed training on HPC systems and tools for training diagnostics and observability potentially integratingphysics-aware constraints and generative modelling approaches.

Both tracks interact closely to create adatamodel feedback loop enabling systematic analysis of how scientific data model architectures and training dynamics influence scientific predictions. You will join avibrant research environment at TU/eat the intersection ofAI scientific computing and computational science collaborating with leading European research groups and benefiting fromadvanced GPU and HPC infrastructure.

Job Requirements

We are looking for researchers excited to work at the intersection ofmachine learning scientific computing and large-scale scientific data. You have:

• A PhD in Computer Science Machine Learning Applied Mathematics Scientific Computing Data Engineering or a closely related field.
• Demonstrated ability to conduct high-quality academic research reflected in publications or other research outputs.
• Strong programming skills in Python and experience with scientific computing environments.
• Experience in one or more of the following areas:
  • machine learning or deep learning (e.g. PyTorch)
  • scientific data pipelines or large datasets
  • knowledge graphs or structured data systems
  • GPU or distributed computing
  • scientific machine learning or physics-informed ML
• Experience working with Linux and HPC environments is an advantage.
• Strong communication skills and excellent proficiency in English.

You enjoy working in aninternational interdisciplinary team mentoring students and contributing to ambitious collaborative research projects.

Conditions of Employment

A meaningful job in a dynamic and ambitious university in an interdisciplinary setting and within an international network. You will work on a beautiful green campus within walking distance of the central train addition we offer you:

• Full-time employment for 1 year with an extension of another year after a positive evaluation.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities scale 10 (min. 4241 max. 5538).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs on general skills didactics and topics related to research and valorization.
• An excellent technical infrastructure on-campus childrens day care and sports facilities.
• Unlimited access to the modern oncampus TU/e Student Sports Center at an exceptionally affordable rate for you and if applicable your partner.
• Partially paid parental leave and an allowance for commuting working from home and internet costs.
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network and offers tailored support training and workshops.
• A Staff Immigration Team is available for international candidates as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.

About us

We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact today and in the future. TU/e is home to over 13000 students and more than 7000 staff forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven a worldleading tech region with more than 7000 hightech companies and strong R&D activity. Known for breakthroughs in AI photonics semiconductors and advanced manufacturing Brainport is a place where technology serves people and society. Learn more about the Brainport region here.

With over 110 (assistant associate and full) professors almost 300 PhD and EngD students about 1500 Bachelor students and 1000 Master students the Department of Mathematics and Computer Science (M&CS) is the largest department of the TU/e. By performing top-level fundamental and applied research and maintaining strong ties with industry M&CS aims to contribute to science and innovation in and beyond the region.

Information

Do you recognize yourself in this profile and would you like to know more Please contact the hiring manager Prof. V. Dolean-Maini .

Visit our website for more information about the application process or the conditions of employment. You can also contact HR services M&CS .

Are you inspired and would like to know more about working at TU/e Please visit our career page.

Application

We invite you to submit a complete application using the apply-button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.
• List of up to five self-selected best publications.

Ensure that you submit all the requested application documents. Please note that incomplete applications may not be considered and could be rejected.

We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.