POST-DOCTORAL POSITION WITHIN THE PROJECT

«Physics-informed Artificial Intelligence for Cognitive Twins of Complex Systems»

The Applied Mechanics and Bioengineering (AMB) group of the University of Zaragoza (see http://amb.unizar.es) is one of the leading groups within the computational mechanics community at a national and European levels, comprised by 20 senior faculty members and a variable number of Ph.D. students and post-doctoral associates.

The group has a broad experience in the development of advanced simulation techniques such as meshless methods, model order reduction and, more recently, scientific machine learning for the simulation of complex, multi physics and multiscale phenomena.

With the recently awarded project Physics-informed Artificial Intelligence for cognitive twins of complex systems we aim at developing novel tools for the machine learning of complex physical phenomena with guaranteed physical meaning.

In the frame of this emergent project in the group, we seek a highly motivated postdoctoral candidate to develop and implement artificial intelligence tools able to achieve physical perception and reasoning about complex physical phenomena taking place in the neighborhood of this AI.

ROLE SUMMARY: 

The candidate, in close collaboration with profs. E. Cueto, D. González, I. Alfaro, and the rest of the team, will develop advanced AI techniques based on physics-informed neural networks towards the creation of cognitive digital twins, able to understand the surrounding environment and adapt to changing scenarios. 

CONTRACT DETAILS: 

Applications/interviews: Please send an email expressing your interest, together with a CV to Prof. Elías Cueto (). Reviews of applications will continue until the position is filled.

Initial date: As son as possible. 

Duration: 2 years. 

Dedication: Full-time, 40 h/week. 

Gross annual salary: 42983 € (including Spanish public health and social security benefits). 

SKILLS / QUALIFICATIONS: 

Hard / Essential: 

• PhD in Computational Continuum Mechanics (or similar), with a strong numerical focus on mathematical modeling. 
• In-depth, hands-on knowledge of modeling software and computer programming (MATLAB, Python, C/C++, Fortran) as well as of the Finite Element Method and its procedures. 

Hard / Desirable: 

• Knowledge about neural network programming (preferably, PyTorch).
• Knowledge on Computer Vision.
• Computational Solid Mechanics. 
• Image Processing and Data Analysis. 

Soft / Essential: 

• Keen interest in learning novel computational methods. 
• Self-directed with the ability to work independently. 
• At the same time, ability to work in group and (co-)advise doctoral students.
• Excellent communication and writing skills in English. 

CONTACT: 

If interested, please send your CV, a cover letter, and a reference letter to Elías Cueto ().

PhD positions at Purdue – Computational biomechanics and fluid dynamics

We have several openings for a PhD positions. The successful candidate will conduct original research in the general area of biomechanics and fluid dynamics. They develop numerical methods to model coupled processes on high-performance computing platforms. This position is in the Gomez Research Group (https://engineering.purdue.edu/gomez/) in the Department of Mechanical Engineering at Purdue.

Applications

Please send an email expressing your interest, together with a CV to Prof. Hector Gomez (). Reviews of applications will start on October 14, 2022 and continue until the position is filled.

Information

You may find some information about Purdue University at https://www.usnews.com/best-graduate-s hools/top-engineering-schools/eng-rankings

https://www.youtube.com/purdue/videos

Postdoc/Scientific programming engineer in high- performance computational mechanics

The group on “Mechanics of soft and living interfaces” (https://www.lacan.upc.edu/mechanics-of-soft-and-living-interfaces/) lead by Professor Marino Arroyo (https://www.lacan.upc.edu/arroyo/) located at the UPC in Barcelona and affiliated to CIMNE and IBEC is seeking a highly skilled postdoctoral researcher or scientific programming engineer to join a software development team and contribute to our in-house C++ high-performance, finite element library called hiperlife. Hiperlife focuses on efficiently and flexibly solving coupled partial differential equations (PDE) on time-evolving surfaces, possibly coupled to bulk PDE, to understand a variety of highly nonlinear multiphysics problems arising from the analysis of thin shell structures, cellular meta-materials, shape-morphing interfaces, and cell and tissue mechanobiology. Our library is based on the Trilinos project, and aims at making advanced mathematical models, highly sophisticated computational technologies, and high-performance computing easily accessible to a wide range of scientists and engineers interested in interfacial problems.

The successful candidate will join a dynamical and interdisciplinary team with a world- class network of collaborators towards:

• Creating the next-generation open-source software for interfacial multiphysics problems (focusing on mechanobiology) across platforms, from desktops to supercomputers
• Develop advanced numerical methods and algorithms required to address cutting-edge scientific multidisciplinary problems
• Deploy state-of-the-art, open-source software that will be used on a daily basis by a wide range of researchers around the world to advance science.Required qualifications

• Strong skills in C++ programming and in unix-like operating systems
• Ph.D. in computer science, computational mathematics, computational physics, or computational engineering. Applicants with a pertinent MS and sufficientexperience will be considered.
• Experience and understanding of numerical methods for partial differentialequations.
• Demonstrated software development expertise (e.g., active github account,successful projects, or documented open-source contribution)
• Enthusiasm for programming, learning, problem solving, and tracking otherlibrary trends
• Exceptional collaboration and communication skills, in particular in English
• Understanding of computer systems, programming language constructs, and design patterns

Preferred qualifications

• Familiarity with high-quality software practices (test-driven development, documentation, software review processes, and cross-platform support).
• Experience with linear algebra libraries (Trilinos/PETSc)
• Experience with large-project build systems (e.g. CMake)
• Familiarity with revision control systems (e.g. git)
• Experience with MPI or multi-threaded programming
• Understanding of the finite element methodCandidates lacking some of the required qualifications but with a strong motivation to expand their expertise will be considered.You will have access to state-of-the-art computing facilities, a generous travel allowance for conferences and specialized training, and will be given the freedom to develop your own ideas and collaborate within the group and with other groups.Besides Skype interviews, it is possible to arrange on-site visits to the lab and the campus in Barcelona. The starting date is flexible during the summer/autumn of 2022. We offer initially a one-year contract, with the possibility of extending it based on the candidate’s performance.Interested applicants are encouraged to send as soon as possible a CV with a list of at up to 3 references and a very concise statement describing your past research/technical experience and your interests. This and specific inquiries should be addressed to Marino Arroyo () and Pablo Sáez () with “Postdoc/Scientific programming engineer-2022” in the subject line.Located in the city of Barcelona, the Universitat Politècnica de Catalunya -BarcelonaTech (UPC) is one of the largest technical universities of southern EU, with over 30,000 students spanning all levels from undergraduate to PhD, and employing over 2,500 faculty. Within UPC, the LaCàN research center develops new mathematical and computational models to enable quantitative and predictive science and engineering, specifically in the field of cell and tissue mechanobiology.