Internship - Computational Methods (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: P531V44P3
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

Explore a remote Computational Methods internship at Confidite, enhancing energy management and sustainability through advanced simulations.

Duties & Responsibilities
  • Develop and implement computational models to optimize energy systems and improve sustainability outcomes.
  • Analyze complex datasets to support engineering solutions for renewable energy and safety enhancements.
  • Collaborate remotely with multidisciplinary teams to simulate and validate energy management strategies.
  • Prepare technical reports summarizing computational findings for research and development initiatives.
  • Utilize advanced software tools to assess environmental impacts and system performance in engineering projects.
Requirements
  • Recent graduates or enrolled in final year of bachelor’s program in engineering or science.
  • Basic proficiency in computational tools (e.g., MATLAB, Python, or similar) and a willingness to expand expertise.
  • Strong analytical mindset with an interest in applying computational methods to real-world energy challenges.
Skills and Knowledge You Gain
  • Proficiency in computational modeling and simulation techniques for energy and engineering applications.
  • Enhanced understanding of sustainable energy systems and their optimization through data-driven methods.
  • Experience with industry-standard software tools used in energy management and environmental engineering.
  • Ability to interpret and communicate complex computational results effectively to technical and non-technical stakeholders.