Masterand
Tenneco-Automotive
| Company | Tenneco-Automotive |
| Category | Uncategorised |
| Location | — |
| Remote | — |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| First seen | 3 Aug 2026 (the employer did not state a posting date) |
| Last verified | 8 Aug 2026 |
| Source | The employer's own careers page (company_site) |
Description
Date: Jul 21, 2026
Location:
Glinde, DE
Company:
Tenneco
Tenneco ist eines der weltweit führenden Unternehmen in der Entwicklung, Herstellung und Vermarktung von Produkten für die Automobil- und Schienenfahrzeugbranche.
Im Geschäftsbereich Tenneco Braking wird eines der breitesten Portfolios an Reibmaterialien für Pkw, Nutzfahrzeuge, Schienengüter- und -personenverkehr, Industrie- sowie Motorsport angeboten. Die Produkte unterstützen Tier-1-Zulieferer und OEMs dabei, aktuelle und zukünftige Umweltanforderungen zu erfüllen.
Für den Standort Glinde (Schleswig-Holstein) wird ein/e Masterand (m/w/d) im Bereich Data, AI & Analytic gesucht. Der Beschäftiungsumfang umfasst 2 Monate Praktikum mit anschließender Masterarbeit über 6 Monate.
Aufgaben:
• Analyse und Strukturierung von Versuchs- und Materialdaten (Rezepturen, Prozessparameter, Performancekennwerte)
• Aufbau und Validierung von Regressionsmodellen (z. B. neuronale Netze, Random Forest, Gradient Boosting) zur Vorhersage von Reibwertverhalten.
• Feature Engineering auf Basis von Materialzusammensetzung und Prozessparametern
• Untersuchung von Generalisierungsfähigkeit und Extrapolation auf neue Rezepturen
• Vergleich unterschiedlicher Modellansätze hinsichtlich Vorhersagegenauigkeit, Robustheit und Interpretierbarkeit
• Identifikation relevanter Einflussgrößen mittels Feature Importance / Sensitivitätsanalysen
• Dokumentation und Präsentation der Ergebnisse
• Enge Abstimmung mit R&D-Ingenieuren zur Sicherstellung physikalischer Plausibilität
Qualifikation:
• Masterstudium in Data Science, Mathematik, Ingenieurswissenschaft oder vergleichbar
• Gute Kenntnisse in: Python ML Frameworks (z. B. scikit-learn, PyTorch oder TensorFlow), Datenanalyse (pandas, polars, NumPy)
• Verständnis statistischer Modellierung und Regressionsverfahren
• Grundkenntnisse in neuronalen Netzen und Overfitting-/Regularisierungskonzepten
• Idealerweise Erfahrung mit: Zeitreihenanalyse, Materialdaten oder physikalischen Modellen, Feature Engineering in technischen Datensätzen
• Strukturierte und selbstständige Arbeitsweise
• Interesse an interdisziplinärer Arbeit zwischen Data Science und Materialentwicklung
• Sehr gute Deutsch- oder Englischkenntnisse
Opens in a new tab.
Opens in a new tab.
Opens in a new tab.
×
When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. However, blocking some types of cookies may impact your experience of the site and the services we are able to offer.
Required Cookies
These cookies are required to use this website and can't be turned off.
Required Cookies
Show More Details
Required Cookies
Provider
Description
Enabled
SAP as service provider
We use the following session cookies, which are all required to enable the website to function:
• "route" is used for session stickiness
• "careerSiteCompanyId" is used to send the request to the correct data center
• "JSESSIONID" is placed on the visitor's device during the session so the server can identify the visitor
• "Load balancer cookie" (actual cookie name may vary) prevents a visitor from bouncing from one instance to another
Functional Cookies
These cookies provide a better customer experience on this site, such as by remembering your login details, optimizing video performance, or providing us with information about how our site is used. You may freely choose to accept or decline these cookies at any time. Note that certain functionalities that these third-parties make available may be impacted if you do not accept these cookies.
Consent to all Functional Cookies
Show More Details
Functional Cookies
Provider
Description
Enabled
Vimeo
Vimeo is a video hosting, sharing, and services platform focused on the delivery of video. Opting out of Vimeo cookies will disable your ability to watch or interact with Vimeo videos.
Consent to cookies from provider Vimeo
YouTube
YouTube is a video-sharing service where users can create their own profile, upload videos, watch, like, and comment on videos. Opting out of YouTube cookies will disable your ability to watch or interact with YouTube videos.
Consent to cookies from provider YouTube
Advertising Cookies
These cookies serve ads that are relevant to your interests. You may freely choose to accept or decline these cookies at any time. Note that certain functionality that these third parties make available may be impacted if you do not accept these cookies.
Consent to all Advertising Cookies
Show More Details
Advertising Cookies
Provider
Description
Enabled
AddThis
AddThis is a widget that allows you to share jobs across the web to various other platforms. Opting out of AddThis cookies will remove your ability to view and use this widget.
Consent to cookies from provider AddThis
LinkedIn
LinkedIn is an employment-oriented social networking service. We use the Apply with LinkedIn feature to allow you to apply for jobs using your LinkedIn profile. Opting out of LinkedIn cookies will disable your ability to use Apply with LinkedIn.