Undergraduate Student

hace 2 semanas

Barcelona, España Barcelona Supercomputing Center (BSC) A tiempo completo

**Job Reference**:

- 332_24_CASAE_WP_R0**Position**:

- Undergraduate Student - PINNs for pressure wave propagation in heterogeneous media (R0)**Closing Date**:

- Wednesday, 05 June, 2024**Reference**: 332_24_CASAE_WP_R0**Job title**: Undergraduate Student - PINNs for pressure wave propagation in heterogeneous media (R0)**About BSC**
- The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 900 staff from 55 countries.
- Look at the BSC experience:

- BSC-CNS YouTube Channel
- Let's stay connected with BSC Folks-
**Context And Mission**
- The student intern will focus on how to reduce the computational cost of physics-based simulation of acoustic wave in various propagation media, by means of Physics-Informed Neural Networks (PINNs). Neural networks are seen as universal function simulators capable f approximating the PDF's solution function. In this work the NNs will be designed and trained to take in account physical laws, boundary conditions as well as propagation medium heterogeneity.**Key Duties**
- Become familiar with several concepts:

- the wave equation and the impulsive response of an isotropic elastic medium

(Helmholtz equation for acoustic wave propagation in 2D) in the presence of a point source.
- its solution and Python implementation using finite differences, in order to be able to generate training data for machine learning purposes.
- Explore how to:

- implement the physics-based Helmholtz equation's solution using finite differences
- implement an FFNNs using available Python libraries and framework, e.g.,

TensorFlow, to solve the corresponding PDEs
- distribute and/or parallelize the training of the FFNN, using BSC’s supercomputing infrastructure, namely either the ACC of GPP partitions of Marenostrum 5 (MN5) for homogeneous propagation media, specifying boundary conditions (BCs) implicitly in the training data and plotting result and errors specifically with regard to BCs.
- Parametrize the propagation media and include the possibility of smoothly varying material properties in both the physics based finite difference code, as
well as in the FFNN (PINN).
- Prepare a situation and final report to be delivered on the last day of the student's interneship. The report should include (i) a structured bibliography on salient questions relevant to the technical work to carry out, (ii) a description of methodologies used throughout the interneship, (iii) any developped code, and (iv) results.

**Requirements**:

- Education
- Essential Knowledge and Professional Experience
- Relevant scientific project experience gained through recent academic courses are positively valued in the following areas: complex data analysis, machine learning, deep learning, high performance computing, distributed computing paradigms (e.g. OpenMP, OpenACC, MPI)
- Additional Knowledge and Professional Experience
- Fluent written and spoken English
- Collaborative and version controlled work environments (e.g. gitlab, github, etc.)
- Unix/Linux and any related scripting shell
- Python 3, C/C++
- Differential calculus
- Basic solution of the Helmholtz equation and qualitative concepts pertaining to wave propagation, useful in describing the dynamic behavior of waves, including phenomena such as wave dispersion, wave interference, and the generation of harmonics.
- Competences
- Good communication and presentation skills.
- Ability to work both independently and within a team.

**Conditions**
- The position will be located at BSC within the CASE Department
- We offer a full-time contract (37.5h/week), a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, extensive training plan, restaurant tickets, private health insurance, support to the relocation procedures
- Duration: Open-ended contract due to technical and scientific activities linked to the project and budget duration
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
- Starting date: 01/07/2024

**Applications procedure and process**- A full CV in English including contact details
- A Cover Letter with a statement of interest in English, including two contacts for further references - Applications without this document will not be considered

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