Eligibility requirement: Interns must have a strong understanding of computers and their use, along with a basic knowledge of statistics and experience in Python or LabVIEW Programming. This internship is conducted in English. High School graduates aged 18+ may be accepted, depending on the strength of their application (including any relevant experience, with a desire to learn and grow within this field).

Language requirements: This internship is conducted in English.

Associated career paths: Electrical / Electronic Engineering, Systems Engineer, Data Analyst, Chemical Engineer, Software Engineer

Internship details

Data Analysis & Machine Learning remote internships are perfect for anyone interested in instrumentation or measurement systems. Interns are matched with technical consultancy firms, which work in the fields of industrial research and education. Remote interns learn about image classification, nanomaterials and customized laboratory software for data acquisition.

This is a remote internship you can conduct from home.

This Data Analysis & Machine Learning remote internship is focused on the fields of Engineering and Computer Science. If you have an interest and background in engineering, data processing, and software development, then you are an ideal participant for this internship.

As an intern, you’ll be matched with a technical consultancy firm that supports industrial research and educational activities in the marine, automotive and agricultural sectors. You can focus your internship on either image classification and analysis of nanomaterials, or customized laboratory software for data acquisition.

When interning in image classification and nanomaterial analysis, you’ll gain valuable skills in understanding and assessing images, and learning recognition techniques. You’ll learn about the classification of a range of material, including nanomaterial and marine/aquarius species, and gain experience developing industrial grade data acquisition setups, in order to educate engineers on IoT systems, remote measurement and data collection techniques.

Interns who focus on data acquisition and analysis can expect to gain real-world experience in dynamic activities related to training datasets, extracting information from images, acquiring/analyzing data, and creating professional reports.

If you’re looking to boost your resume, develop your network, and gain real-world software development and engineering experience that can complement your studies, this remote internship provides practical insight into a growing field with broad possibilities.

Remote interns maintain regular contact with your supervisor in Greece through emails and video conferences. Your supervisor will help to give feedback on your progress, to fortify your learning, answer your questions, and provide updates in regard to activities and tasks. This will mean you’ll need to be available for occasional meetings during office hours in Greece.

This internship is conducted in English.

Data Analysis & Machine Learning interns learn from a qualified and experienced supervisor, and can be involved in:
  • Training datasets for image recognition
  • Extracting information from images, for data analysis
  • Acquiring and analyzing sensory data
  • Interfacing with measurement systems and sensors
  • Writing instrumentation code (Python / LabVIEW)
  • Creating reports in Microsoft Office
Professional development opportunities:
  • Gain experience in interfacing with hardware, sensors and instrumentation
  • Writing data acquisition code and analyzing data from images
  • Gain supervision and mentorship from experienced researchers and engineers
  • Gain practical skills and boost your employability, with guidance from Intern Abroad HQ’s Experiential Learning Curriculum to support your learning and cultural intelligence.
Typical schedule:
  • As a remote intern, you’ll have the flexibility to work to a schedule that suits both you and your supervisor. Your schedule will need to accommodate online meetings with your supervisor when it’s required, so there will be times where you’ll need to be available during office hours in Greece.
Internship highlights:
  • Gain hands-on development and computer engineering skills
  • Learn highly specialized image classification, data acquisition and analysis techniques
  • Gain international work experience while interning remotely from home without having to travel
Types of host organizations:
  • Technical consulting companies

Keen to get started?

Taking the first step is easy! It is free to apply and takes just 5 minutes.

Submit an application

Program fees

It’s free to apply for this internship. Once we have reviewed your suitability and accepted you onto this program, you’ll need to pay a deposit of US$449 to confirm your place. The remaining balance of your Program Fee (less your initial US$449 deposit payment) will be due within 7 days of being assigned a placement.

Internship Duration Program Fee (USD)
100 hours (3 weeks full time, or 5 weeks part time) 100 hour options $948
250 hours (8 weeks full time, or 12 weeks part time) 250 hour options $1,348
350 hours (13 weeks full time, or 17 weeks part time) 350 hour options $1,648
  • To convert these prices to your local currency visit the XE currency converter.
  • All payments attract a 5% transaction fee to cover international banking fees and currency charges. International wire transfer payments attract a minimum fee of US$75.
  • Terms and Conditions apply

Program fee for remote internships

What it covers
  • Dedicated support before, during and after your internship
  • Securing your internship placement
  • Personalization of your internship plan
  • Orientation and coaching with your supervisor
  • Experiential Learning Curriculum
  • International reference letter

Intern review: Hailey Shah

Greece - Environmental & Marine Sciences

"My internship was such a valuable experience and I learned so much! The experience gave me the unique opportunity to be involved in literature analysis, research proposal design, data analysis and pre..." read more

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