Internship - Process Reliability Engineering (Remote)

Duration: 1 to 3 months
Application Deadline: 15 May 2025
Eligibility: Bachelor's students and recent graduates
Location: Fully Remote
Stipend: None (unpaid)
Ref: UNMGIMPF7
Internship Highlights
  • Fully Remote: Work from anywhere.
  • Flexible Schedules: Students can select their preferred internship start dates.
  • Learn New Skills: Master industry-standard tools and concepts.
  • Career Experience: Gain real-world skills and enhance your career prospects.
  • Higher Education Support: Receive guidance for pursuing advanced studies.
  • Academic Credits: Earn credits for your degree.
Introduction

Join Confidite’s remote Process Reliability Engineering internship, optimizing energy systems for sustainability and safety.

Duties & Responsibilities
  • Analyze process data to identify and mitigate risks in energy production and management systems.
  • Develop reliability models to enhance the performance and safety of sustainable energy processes.
  • Collaborate remotely with engineering teams to implement improvements in process efficiency.
  • Conduct statistical assessments to predict and prevent failures in energy-related operations.
  • Prepare technical reports detailing reliability findings for Confidite’s engineering and R&D initiatives.
Requirements
  • Recent graduates or enrolled in final year of bachelor’s program in engineering or science.
  • Basic proficiency in statistical analysis or engineering principles, with a desire to deepen expertise.
  • Analytical mindset and interest in improving process reliability for sustainable energy solutions.
Skills and Knowledge You Gain
  • Expertise in reliability engineering techniques for optimizing energy and industrial processes.
  • Proficiency in statistical modeling and data analysis to enhance system safety and performance.
  • Understanding of sustainable energy systems and their operational reliability requirements.
  • Ability to communicate process reliability insights effectively to support engineering decisions.