Master thesis: Fine-Tuning Foundation Models for Energy-Efficient 5G Orchestration

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · DevOps

In short

This Master thesis project focuses on adapting time series foundation models for energy-efficient 5G orchestration by fine-tuning them on cloud-native network function telemetry metrics. The goal is to develop accurate forecasts for proactive network management, reducing over-provisioning and energy waste.

Responsibilities

Investigate adaptation of time series foundation models (e.g., TimesFM, TTM) to cloud-native 5G NF telemetry.
Conduct data collection from lab and testbed environments.
Perform systematic evaluation of foundation models in zero-shot and few-shot settings.
Potentially implement parameter-efficient fine-tuning techniques (LoRA, adapters).
Benchmark foundation models against classical baselines on NF energy, resource usage, and/or traffic prediction.
Develop a fine-tuning methodology for adapting foundation models to cloud-native 5G NF telemetry metrics.
Analyze model generalization across NF types, prediction targets, and training data regimes.
Provide recommendations for integrating foundation model-based forecasting into energy-aware network orchestration pipelines.

Requirements

Background in machine learning, computer science, data science, or a related field.
Strong understanding of deep learning and time series modelling.
Proficiency in Python.
Familiarity with modern ML frameworks (Hugging Face, GluonTS, or similar).
Ability to conduct technical literature reviews, design experiments, analyse results, and document findings.
Strong analytical and problem-solving skills.
Ability to work independently while communicating effectively in an international research environment.
Good written and spoken English.

Desired Qualifications

Experience with PyTorch is advantageous.
Interest in cloud-native systems (Kubernetes, microservices) and sustainable computing.

Benefits

Outstanding opportunity to use your skills and imagination to push boundaries.
Work on building solutions never seen before to tough problems.
Be challenged in a supportive environment with diverse innovators.
Chance to craft what comes next.
Encouraging a diverse and inclusive organization is core to our values.

Skills

PythonPyTorchKubernetesmicroservicesHugging FaceGluonTS

#5G#orchestration#foundation models#energy efficiency#time series forecasting#cloud-native#Kubernetes#machine learning#deep learning#Python

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