Master Thesis Student– Machine Learning On Temporal Graphs (M/F/D)

Job Summary

Huawei, is currently hiring on a vacant job post of Master Thesis Student– Machine Learning On Temporal Graphs (M/F/D) based in München. Please read the job detail carefully before applying.

Job Title: Master Thesis Student– Machine Learning On Temporal Graphs (M/F/D)
Company Name: Huawei
Job Type: Vollzeit
Job Location: München
Salary:
Job Link Expiry: 2022-11-04
Posted on: jobsintelecom.net

Job Detail

Huawei is a leading global information and communications technology (ICT) solutions provider. Driven by a commitment to operations, ongoing innovation, and open collaboration, we have established a competitive ICT portfolio of end-to-end solutions in Telecom and enterprise networks, Devices and Cloud technology and services. Our ICT solutions, products and services are used in more than 170 countries and regions, serving over one-third of the world’s population. With 197,000 employees, Huawei is committed to develop the future information society and build a Better Connected World.

Huawei’s Munich Research Center is responsible for advanced technology research beyond Huawei’s product lines as well as strategic planning, architectural design, and development for our products.

The Huawei Artificial Intelligence for Cyber-Security (AI4Sec) Research Team is responsible for forefront research on machine learning algorithms and cyber-security. We invent, prototype and publish state-of-the-art machine learning-based solutions applied to cyber-security domains that require algorithmic breakthroughs. Our algorithms address open problems in cyber-security, such as network analytics for advanced threat detection, malware detection and information extraction from unstructured data. Algorithmic areas we work in include but are not limited to large-scale data mining, un-, semi- and self-supervise machine learning, network science and graph analytics, geometric deep learning, temporal sequence models, continual and contrastive learning, out-of-distribution detection, reinforcement learning and NLP. In cooperation with Huawei’s product lines, we keep Huawei’s core security technologies ahead of its competition.

 

Now we are looking for a:

Master Thesis Student– Machine Learning on Temporal Graphs (m/f/d)

to join our AI4Sec Research Team in Munich for 6 months.

 

Depending on the applicant’s strengths and interests, the master thesis project will focus on temporal graph neural networks, robust community detection, anomaly detection, temporal point processes on graphs or a related topic.

Responsibilities

• Study and summarize research literature related to your research project
• Design algorithmic ideas addressing open research challenges related to your topic
• Develop a well-documented prototype in Python
• Conduct and document comprehensive experiments on internal as well as synthetic and public datasets

 

Requirements

• Enrolled in an Master’s program in Computer Science or other related disciplines
• Profound knowledge in machine learning
• Proficiency in Python and deep learning frameworks (PyTorch, JAX or Tensorflow)
• Strong motivation in conducting publishable research on graph machine learning that addresses problems in the cyber-security domain
• Fluency in written and spoken English

What you can expect

• Our culture is characterized by innovative power and team spirit as well as the intensive exchange of knowledge and experience within our global network.
• We offer you a competitive compensation package and a broad range of training opportunities. Many online and face-to-face training programs.

Self-responsible work in a competent, motivated and constantly growing team

If you are enthusiastic to shape the Research Center together with us, with a very high level of technical innovation, being part of a multicultural team and growing environment, feel free to contact us.

Please send your application and CV (incl. cover letter and reference letters) in English.

By applying to this position, you agree with our Recruitment Privacy Statement. You can read in full our privacy policy here.

 

 

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