You will work with a team of researchers and developers from UPF. Martí Sánchez Fibla will be the scientific person in charge. You will have the opportunity to directly interact with the innovation line of the company but from the university and with a research focus.
You will be working in the project Matching Learning (red.es BMAT-UPF) in close collaboration with the company BMAT (en.wikipedia.org/wiki/BMAT_Music_Company). BMAT is a music company that uses artificial intelligence to index, monitor and report music usage and ownership data across TVs, radios, venues and digital platforms worldwide.
This offer gives the opportunity to work on a highly new and innovative field: the application of state of the art Natural Language Processing tools based on Deep Learning and Large Language Models (GPTx and open source versions of ChatGPT) to process (semi and unstructured) data.. The challenges that you will be addressing will be realistic and relevant for industry as they will be provided directly from BMAT.
These tasks are related to completion of the project by 30/05/2024. The concrete tasks to be accomplished are:
- T1. Intelligent meta-data matching. Develop python software based on Deep Learning techniques (through Deep Neural Networks, DNNs as transformers networks, through the use of the so-called Embeddings) to resolve the matching problems of metadata that the company has identified. Datasets will be provided and different techniques will be implemented, tested and benchmarked.
- T2. Develop specific methods for a specific use-case. Do specific training of DNNs to solve the metadata matching problems in a specific domain: for example the Music Production domain. Compare how a specific fine tuning of DNNs can solve the tasks better. Evaluate and benchmark results.
Dedication and working hours: Part time (30h/week)
Planned remuneration approx: 27.280,86 € gross / year
Main research field: Artificial Intelligence / Natural Language Processing
Project: Motor de reconciliación de entidades impulsado por IA para la industria de la música (Matching Learning)
Financing fund: CN08722 – BMAT LICENSING, S.L.U.-Martí Sánchez Fibla- Realización del proyecto consistente en aplicar los recientes resultados en investigación en Inteligencia Artificial del procesado del lenguaje aportados por UPF, a la gran cantidad y diversidad de datos en el dominio de producción musical de BMAT, the project ends on 30/05/2024.
- Research Field
- Computer science
- Education Level
- Bachelor Degree or equivalent
We will value:
- Experience in Natural Language Processing (NLP) programming techniques.
- Knowledge of specific NLP libraries like Hugging Face transformers API.
- The position has a research focus so we will value the ability to read, understand and be able to use code from research papers of the field. Example of papers that can be relevant: “Efficient Estimation of Word Representations in Vector Space”, Mikolov et al., 2013; “Attention is all you need”, Vaswani et al., 2017.
- Engineer with an undergraduate degree (or equivalent) in Computer Science or related disciplines, with a Final Project related to the field.
- Previous contact with the academic world either: having done a Master Thesis in a related topic or an internship in a research group or an internship in a company.
- Proficiency in Python programming will be required and proven experience with deep learning in any of the libraries tensorflow / keras / pytorch.
- Good English Level, reading and writing.
The expected start date is 10 Novembre 2023, the job is in Barcelona, and Nie and a work permit is required and in case of not having it, demonstrate being in a process of renewal of visa and having a residency in Barcelona one week previous to the start.
The selection of the candidates will be made through evaluation of the curriculum and, where appropriate, with the carrying out a test and/or interview. Valuation will be as follows:
- Academic background: 30 points.
- Relevant research and/or professional experience: 50 points – Experience in Natural Language Processing. (NLP) programming technique.
- Other merits: 20 points – Knowledge of specific NLP libraries like Hugging Face transformers API., The position has a research focus so we will value the ability to read, understand and be able to use code from research papers of the field. Example of papers that can be relevant: “Efficient Estimation of Word Representations in Vector Space”, Mikolov et al., 2013; “Attention is all you need”, Vaswani et al., 2017.
The minimum score to pass the selection process is 80 points. The candidate with the highest score in the selection process will be offered the job and in case of resignation, the position will be awarded to the next person in order of score obtained, as long as the established minimum score has been passed.
For more information about the call, how to apply, the list of those admitted and excluded, as well as the hiring proposal, check the website: https://www.upf.edu/web/etic/management
|Job Category||Enseignement et recherche scientifique|