Short-term Research Project on Network Data Representation

Fecha: 29 mar. 2024

Ubicación: BARCELONA, ES

Empresa: Telefonica S.A.

 

Telefonica Innovación Digital - Discovery Research is hiring for a short-term research project focused on Network Data Representation. 
 

Telefonica Innovación Digital - Discovery Research is a leading industrial research lab based in Spain (Barcelona and Madrid). At Telefonica Innovación Digital - Discovery Research, we follow an open research model in collaboration with Universities and other research institutions, promoting the dissemination of scientific results both through publications in top-tier peer-reviewed international journals and conferences and technology transfer. Our multi-disciplinary and international team counts several full-time researchers, holding PhD degrees in various disciplines of computer science and electrical engineering. 
 
We are looking for a researcher (close to finishing their PhD or in early stages after the PhD) to join our team of experts who are working on cutting edge solutions for network flow trace generator. During this short-term project, which can last up to 6 months, the researcher will be responsible for designing and implementing deep learning solutions that can capture the dynamic characteristics of network traffic.
 
Key Responsibilities:

  • Design and develop models to generate realistic network data, with high fidelity (e.g., capture spatio-temporal correlations in multivariate time series data, or correlations in tabular network data).
  • Conduct experiments to evaluate the accuracy and fidelity of network data generation models.
  • Implement state-of-the-art techniques such as differential privacy and homomorphic encryption to ensure user privacy.
  • Stay up to date with industry trends and developments related to generative deep learning models and make recommendations for future improvements.
  • Write technical reports and documentation to communicate results to internal and external stakeholders.
     

Qualifications:

  • PhD (or close to completion) in Computer Science, Electrical Engineering, or related field.
  • Very good record of research output (e.g., publications in top conferences and journals).
  • Strong experience in data science, and machine learning applied to networks, and ideally some experience with generative deep learning.
  • Knowledge of network data characteristics, networking architecture, traffic models.
  • Strong programming skills in languages such as Python, and Deep Learning libraries such as PyTorch and TensorFlow.
  • Experience with large-scale data processing tools (e.g., Spark) is a plus.
  • Excellent analytical and problem-solving skills.
  • Strong communication and interpersonal skills to collaborate with cross-functional teams.

 

#UnidadesGlobales #CDO

 

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