20 beste Stellen als student machine in münchen – aktuell auf Personalsuche

Working Student- Ecodesign
The Exploration Company —München
- 16 € – 18 € pro Stunde
- Informatik
- Python
- Umzugskostenzuschuss
7 Std.
Working Student Machine Learning (all genders)
Avelios Medical GmbH —München
- Teilzeit
- Machine Learning
- Künstliche Intelligenz
- Python
- Flexible Arbeitszeiten
Working Student Machine Learning (all genders)
Avelios Medical —München
- Teilzeit
- Machine Learning
- Künstliche Intelligenz
- Python
- Flexible Arbeitszeiten
AI Internship / Working Student
Resaro AI —München
- Hybrides Arbeiten
- Informatik
- Master
- Bachelor
Direkt bewerben
Working Student AI-Driven Automated Testing (f/m/x)
BMW —München
- Teilzeit
- Informatik
- Java
- Machine Learning
- Flexible Arbeitszeiten
Intern AI and Machine Learning at Rolls-Royce Motor Cars (f/m/x)
BMW —München
- Vollzeit
- Master
- Machine Learning
- Künstliche Intelligenz
- Flexible Arbeitszeiten
Intern Artificial Intelligence (m/f/d)*
Munich Re —München
- Vollzeit
- DevOps
- Master
- Bachelor
Ground Systems Working Student (m/f/d)
Isar Aerospace SE —München
- AutoCAD
- CAD
- Systemdesign
Direkt bewerben
Working Student (m/f/d) Data Science Computer Vision / IdentityCheck
CHECK24 —München
- Teilzeit
- Informatik
- Machine Learning
- Python
- Flexible Arbeitszeiten
- Kostenlose Verpflegung
Working Student – Software Team (m/f/d)
LivaNova —München
- Teilzeit
- Informatik
- Englisch
- C++
Working Student IT Applications (m/f/d) - onsite
LivaNova —München
- Teilzeit
- Informatik
- Datenanalyse
- Englisch
- Flexible Arbeitszeiten
10 Tage
Working Student - HW development Test development & Automation (f/m/div)
Infineon Technologies AG —München
- Teilzeit
- CAD
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- Bachelor
Data Science Intern (all genders)
SKD SE —München
- Teilzeit
- Azure
- Informatik
- Datenanalyse
13 Tage
Sales Intern / Working Student (f/m/d)
ClearOps GmbH —München
- Teilzeit
- CRM-Software
- Vertrieb
- Unternehmensentwicklung
- Flexible Arbeitszeiten
Direkt bewerben
Working Student / Intern - Post-Training for Robot Learning
Animore —München
- Informatik
- Englisch
- Master
Direkt bewerben
10 Tage
Intern Physical AI - Imitation Learning (f/m/x)
BMW —München
- Vollzeit
- Informatik
- Machine Learning
- Künstliche Intelligenz
- Flexible Arbeitszeiten
Working Student – Gen AI (f/m/div)
Infineon Technologies AG —München
- Teilzeit
- Master
- Künstliche Intelligenz
- Python
2 Tage
Intern AI Solutions Engineering (f/m/x)
BMW —München
- Vollzeit
- Informatik
- Windows
- AWS
- Flexible Arbeitszeiten
Intern/Working Student (m/f/d) Tax Technology, Automation & AI
Allianz —München
- Teilzeit
- Azure
- Informatik
- Machine Learning
Working Student – Battery Science and Data (f/m/d)
Munich Electrification —München
- Vollzeit
- Datenanalyse
- SQL
- AWS
- Homeoffice-Möglichkeit
Direkt bewerben

Ich möchte aktuelle Job-E-Mails für Stellen als student machine in münchen erhalten

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student machine jobs near münchen

Working Student- Ecodesign

The Exploration Company -
München

Jetzt bewerben

Details zur Stelle

16 € – 18 € pro Stunde
vor 7 Stunden

Leistungen

Umzugskostenzuschuss

Qualifikationen

Informatik
Systems Engineering
Python

Vollständige Stellenbeschreibung

Here at The Exploration Company, we are developing, producing, and operating Nyx, a modular and reusable space orbital vehicle that can eventually be refuelled in orbit and that can carry cargo - and potentially humans in the longer run.

We are looking for a motivated working student to join us as a Working Student- Ecodesign to help in our LCA tools.

Tasks

As our Ecodesign Working Student, your role will evolve alongside our projects and ambitions. On a day-to-day basis, you'll be:

Improving and expanding our internal Life Cycle Assessment (LCA) tools, refactoring Python scripts to make them more robust, modular, and easier to build on over time.
Supporting the integration of AI agents into our Ecodesign and LCA workflows.
Keeping our scripts and data pipelines up to date with the latest LCA standards, so that results are traceable, reproducible, and hold up to scrutiny.
Running Life Cycle Assessments on actual projects, products, and components in development at The Exploration Company.
Identifying where our environmental footprint is largest, across materials, manufacturing, operations, and end-of-life, and flagging where improvements are possible.
Quantifying the environmental impact of design decisions, comparing scenarios, and presenting trade-offs with clear assumptions and sensitivity checks.
Contributing to how we develop and document LCA methodologies internally, so that others across the company can run consistent, reliable assessments.
Presenting your findings to both technical and non-technical colleagues, and translating what the numbers mean into concrete, actionable recommendations.

Qualifications & Background

Bachelor's or Master's student in Computer Science, Engineering, Environmental Science, Sustainability, or a related field, with a solid technical foundation.
Good Python skills and a strong interest in writing code that's clean, well-documented, and maintainable.
Some familiarity with Life Cycle Assessment and Ecodesign, or a genuine willingness to dive into it quickly.
Prior experience, hands-on or academic, with LCA tools or sustainability methodologies is a plus.
A background in material science, space systems engineering, or product design is welcome.
Knowledge of AI or machine learning is a strong bonus, particularly if you're keen to apply it to LCA data challenges.

Skills & Behaviours

Comfortable working independently as well as within cross-functional teams, and able to collaborate effectively with engineering colleagues.
An analytical mindset with genuine curiosity. You don't mind working with incomplete or imperfect data, and you find complex sustainability problems interesting rather than daunting.
Detail-oriented and thorough in documentation and reporting, with a focus on reproducibility and being explicit about assumptions.
A constructive, solutions-focused attitude that fits with The Exploration Company's values: Commitment, Innovation, Trust, Quality, and Teamwork.

Why you should join us!

What makes us special here at The Exploration Company and why we think you will enjoy working here is:

We’re Agile - we make decisions fast whilst keeping our goals and systems in mind
We’re Open and Collaborative - we are transparent about risks and obstacles, so that we can cooperate to overcome them
We have a lot of Fun - we refuel our energy knowing we are democratising space. It’s a wonderful and rare opportunity, are YOU up for the challenge?

We'd love to hear from you if you wish to be a part of our journey. Please submit your CV now for immediate consideration and we will be in touch shortly.

The Exploration Company is an equal opportunity employer and values diversity. We do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status. Relocation assistance is provided for those willing to relocate including visa sponsorship where applicable.

All offers are contingent upon the successful completion of a background check, which will be subject to the country, role, and project you applied for. By submitting your application, you acknowledge and agree that any offer of employment may be conditional upon successful condition of this check. The Exploration Company partners with Zinc Work Limited located in the UK (Zinc), a third-party provider, to ensure this process as efficient and transparent as possible.

If applicable, you will receive an email from Zinc upon acceptance of your offer with a link to a secure portal where you can provide the required information to Zinc.

Jetzt bewerben

Erweiterte Suche

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Working Student- Ecodesign

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Intern Physical AI - Imitation Learning (f/m/x)

Working Student – Gen AI (f/m/div)

Intern AI Solutions Engineering (f/m/x)

Intern/Working Student (m/f/d) Tax Technology, Automation & AI

Working Student – Battery Science and Data (f/m/d)

Ich möchte aktuelle Job-E-Mails für Stellen als student machine in münchen erhalten

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