1

Learning Network Jobs in Minnesota (NOW HIRING)

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Social Networking tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Social Networking tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Social Networking tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Showing results 41-60

Learning Network information

What is a learning network?

A Learning Network job typically involves facilitating knowledge-sharing and collaboration among individuals or organizations. Professionals in this role design, implement, and support learning initiatives, often leveraging digital platforms and communities. They help connect people, curate resources, and foster a culture of continuous learning. This may be done within companies, educational institutions, or industry groups. The goal is to enhance skill development and knowledge exchange across participants.

What are the main responsibilities of someone working in a learning network position?

In a Learning Network role, you are primarily responsible for connecting educators or professionals to share best practices, resources, and knowledge within an organization or across institutions. This often involves designing and facilitating virtual or in-person learning events, managing online communities, and curating educational content. You'll collaborate closely with subject matter experts, IT teams, and stakeholders to ensure the network meets the evolving needs of its members. The role can be both strategic and hands-on, offering opportunities to shape learning culture while directly impacting professional growth.

What are the key skills and qualifications needed to thrive in the learning network position, and why are they important?

To excel in a Learning Network role, you should possess expertise in instructional design, educational technology, and organizational learning, often supported by a degree in education or a related field. Familiarity with Learning Management Systems (LMS), collaboration platforms, and data analytics tools is highly valuable. Strong communication, networking, and facilitation skills help foster knowledge sharing and collaboration across diverse groups. These competencies are crucial for effectively building, maintaining, and optimizing networks that support ongoing professional development and learning initiatives within organizations.

What are the most commonly searched types of Learning Network jobs in Minnesota?

The most popular types of Learning Network jobs in Minnesota are:

What are popular job titles related to Learning Network jobs in Minnesota?

For Learning Network jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Learning Network jobs in Minnesota look for?

The top searched job categories for Learning Network jobs in Minnesota are:

What cities in Minnesota are hiring for Learning Network jobs?

Cities in Minnesota with the most Learning Network job openings:

Infographic showing various Learning Network job openings in Minnesota as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Edge Network Migration Architect for 5G MEC

Virginia, MN โ€ข On-site

$62.25 - $83.50/hr

Other

Posted 27 days ago


Job description

Jul 02, 2026 4 min read

PROJ Service Migration in Cellular Networks

This project has three focus parts: Cellular Networks Testbed, LLMs, and optimization algorithms.

Cellular Networks Testbed

Image from: Real-Time Service Migration in Edge Networks: A Survey

The testbed architecture spans four tiers: Central Cloud, Regional MEC, Aggregation MEC, and Local MEC.Primary focus: Regional MEC and Aggregation MEC.Regional MEC, Aggregation MEC, and Local MEC should be deployed to my PVE Testbed.

Each MEC site (or per Metro (metropolitan area) / PoP (Point of Presence)) needs its own control plane because:

  • Survivability: If WAN/backhaul drops, the site keeps running. A single, stretched cluster loses control-plane access and flakes.
  • Latency/etcd constraints: Kubernetes control-plane (etcd) hates WAN latency/packet-loss; cross-site RTTs >~5-10 ms and jitter cause elections and outages.
  • Blast radius & upgrades: Failures and rollouts stay local, enabling per-site upgrades.
  • Regulatory / tenancy: Site-level isolation simplifies policy and compliance.
TODO Central Cloud

Cloud (Azure)High-level design: Azure Virtual WAN (Standard) with four hubs in a full inter-hub mesh. Regional spokes (AKS VNets) attach to their nearest hub; inter-hub routing provides global any-to-any.

Regions (paired for HA/DR):

  • East US 2 (VA) - primary; paired with Central US (closest to UVA)
  • Central US (IA) - DR for East US 2
  • West US 3 (AZ) - west capacity/DR; paired with East US
  • East US (VA) - additional east capacity and the formal pair for West US/West US 3

(All selected regions provide Availability Zones.)

TODO Regional MEC (e.g., Richmond PoP)

50-200 km coverage | RTT to Aggregation 15-30 msUse cases: smart city, cloud gaming, content deliveryComponents: SMF/AMF/PCF (control plane) + Regional UPF

10-50 km coverage | RTT to Local: 10-20 msUse cases: campus control, local CDN

OKD (3 master nodes)Components: SMF/AMF/PCF (control plane) + optional Aggregation UPF

TODO Local MEC

Components: Local UPFDeploy two OKD SNOs or MicroShift clusters (MEC-1: Campus South; MEC-2: Campus North)

N3 (gNB to UPF @ MEC): VLAN/VRF local to the site, low jitterN6 (UPF to campus/ISP): routed toward the PoP

Digital Twin

Must implement N2, N3, and optionally Xn. Focus on mmWave.

Focus on multi-agent workflow design and LLM fine-tuning.

ETSI = European Telecommunications Standards Institute

Famous work includes ETSI MEC (edge computing) and the original ETSI NFV effort.

Deploy Three LLMs to Regional MEC or Aggregation MEC:

Mobility Predictor Agent (MPA) Aggregation MEC / Local MEC (Near-RT RIC/O-RAN Layer) Context Generation: Provides real-time prediction of UE handover and mobility patterns to anticipate service relocation. Real-time Radio KPIs (RSRP, RSRQ), Handover/Xn/N2 events, UE location/velocity. Proactive Migration: Essential for timely initiation of migration at the lowest latency tiers, ensuring QoE under high mobility.

MEC Resource Agent (RCA) All Managed MEC Sites (Local, Aggregation, Regional) Local State Reporting: Monitors the instantaneous resource utilization and available capacity of its local compute cluster (OKD/MicroShift) CPU/Memory/GPU load, Available network bandwidth, K8s/OKD/MicroShift node metrics. Survivability and Autonomy: Guarantees that every control-plane instance has local resource awareness, upholding isolation and independence

Migration Planner Agent (PLA) Regional MEC and Aggregation MEC (Control Plane) Decision-Making: Determines the optimal migration target, timing, and method based on its scope (Local -> Local vs. Regional -> Regional). Aggregated Predictions (MPA data), Resource Availability (RCA reports), Service SLOs, Migration Cost Model. Hierarchical/Decentralized Decision: Enables ultra-low-latency decision-making for local PoP movements and wide-area optimization, avoiding high Central Cloud RTT

State/Traffic Steering Agent (TSA) Co-located with SMF/UPF Execution & Cutover: Executes the migration by coordinating state transfer and updating the 5G Core traffic rules PLAโ€™s Decision (Target MEC ID), State Transfer Status, 5G Core N4/N11 APIs (for UPF/SMF control plane updates) Critical Service Continuity: Directly implements the necessary 5G Core control procedures (PSA Relocation/UL-CL) at all anchor points to shift traffic seamlessly

Policy Enforcement Agent (PEA) Central Cloud (Azure) Global Policy Management: Distributes high-level, long-term policies, cost objectives, and optimization models across all PLA instances Long-term historical data, Global business objectives, Failure tolerance settings, Regulatory/Tenancy policies. Global Governance: Provides the top-level goals and learning feedback to the decentralized PLA instances, ensuring consistency and alignment with global business objectives.

#J-18808-Ljbffr