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Beachten Sie bitte, dass für Stellen als Postdoktorand(in) oder wissenschaftliche(r) Mitarbeiter(in) auch jederzeit Initiativbewerbungen bei den Professoren unseres Instituts möglich sind.


Wissenschaftliche(r) Assistent(in) / Projektleiter(in) / Habilitand(in)

Stellenausschreibung196
Forschungsgruppe: Cooperative Autonomous Systems (Alexey Vinel)
Beschreibung: Keine Beschreibung verfügbar

Stellenausschreibung216
Forschungsgruppe: Systems, Data, Simulation & Energy (Sanja Lazarova-Molnar)
Beschreibung: Keine Beschreibung verfügbar


Wissenschaftliche(r) Mitarbeiter(in) / Doktorand(in)

Stellenausschreibung178
Forschungsgruppe: Systems, Data, Simulation & Energy (Sanja Lazarova-Molnar)
Beschreibung: Keine Beschreibung verfügbar

Stellenausschreibung197
Forschungsgruppe: Cooperative Autonomous Systems (Alexey Vinel)
Beschreibung: Keine Beschreibung verfügbar

[[Stellenausschreibung205|Die Forschungsgruppe Web Science beschäftigt sich mit der Entwicklung und Anwendung von Methoden der Künstlichen Intelligenz (KI). Hierzu zählt die semantische Wissensrepräsentation durch Wissensgraphen, das maschinelle Lernen und die Verarbeitung natürlicher Sprache.


Sie werden in einem großen, interdisziplinären Team aus den Fachbereichen Produktionstechnik und Informatik in sieben Teilprojekten an grundlegend neuen Lösungswegen forschen, um aufwendigen Entwicklungsphasen neuer Produktionsprozesse durch den gezielten Einsatz von Methoden der Künstlichen Intelligenz schneller, kostengünstiger und effizienter zu gestalten.


Zu Ihren Tätigkeiten gehört die Forschung im Bereich semantischer Technologien für die Produktion. Insbesondere sollen Methoden entwickelt werden, um hybride Anfragen über semantische (Faktenwissen) und physikalische Daten (physikalische Modelle mit Grundlagen in Differentialgleichungen) aus Verwaltungsschalen und digitalen Zwillingen mithilfe von KI-Methoden zu beantworten.


Neben den Forschungsarbeiten sind Sie auch in der Lehre aktiv, insbesondere der Künstlichen Intelligenz, und Sie beteiligen sich an der Wissenschaftsverwaltung.


Persönliche Qualifikation

Sie verfügen über eine abgeschlossene Wissenschaftliche Hochschulbildung (Master) des Wirtschaftsingenieurwesens, der Informatik, der Wirtschaftsinformatik, oder in verwandten Bereichen. Sie besitzen idealerweise Erfahrungen in:

  • Semantischen Technologien und symbolischer Künstliche Intelligenz
  • Formalen Methoden zur logischen Modellierung dynamischer Systeme

und interessieren sich für Themen wie

  • Produktion
  • Question Answering
  • Große Sprachmodelle
  • Forschungsdatenmanagement
  • Verwaltungsschalen und Digitale Zwillinge

Von Vorteil sind Programmiererfahrungen. Weiterhin überzeugen Sie durch eine hohe Eigenmotivation und Teamfähigkeit. Sehr gute Deutsch- und Englischkenntnisse in Wort und Schrift runden Ihr Profil ab.


Entgelt

EG 13, sofern die fachlichen und persönlichen Voraussetzungen erfüllt sind.


Eintrittstermin

nächstmöglich


Vertragsdauer

befristet


Fachliche/r Ansprechpartner/in

Für weitere Informationen wenden Sie sich bitte an Herrn Dr. Tobias Käfer


Bewerbung

Bewerben Sie sich bitte mit Ihren aussagekräftigen Unterlagen: Anschreiben, Lebenslauf, Zeugniskopien, idealerweise mit weiteren Angaben wie Masterarbeit bzw. ihrem Entwurf, GitHub-Profil. Nutzen Sie für Ihre Bewerbung das Bewerbungsportal des KIT. Dort ist auch die offizielle Version dieser Ausschreibung zu finden. Die Stellen sind offen, bis sie besetzt sind.

Wir streben eine möglichst gleichmäßige Besetzung der Arbeitsplätze mit Beschäftigten (w/m/d) an und würden uns daher insbesondere über Bewerbungen von Frauen freuen.

Bei gleicher Eignung werden anerkannt schwerbehinderte Menschen bevorzugt berücksichtigt.]]
Forschungsgruppe: Web Science (Tobias Käfer)
Beschreibung: Keine Beschreibung verfügbar

Stellenausschreibung211
Forschungsgruppe: Systems, Data, Simulation & Energy (Sanja Lazarova-Molnar)
Beschreibung: Keine Beschreibung verfügbar

Stellenausschreibung212
Forschungsgruppe: Cooperative Autonomous Systems (Maximilian Schrapel)
Beschreibung: Keine Beschreibung verfügbar

Stellenausschreibung217
Forschungsgruppe: Systems, Data, Simulation & Energy (Sanja Lazarova-Molnar)
Beschreibung: Keine Beschreibung verfügbar


HiWi / Tutor(in)

The research assistants will support the scientific staff of the Systems, Data, Simulation & Energy (SYDSEN) research group. The SYDSEN research group concentrates on the use of data for providing decision support and enhancing energy efficiency, reliability and other performance metrics of cyber-physical systems, such as energy systems or smart manufacturing systems. In particular, our focus is on the development of new methods and approaches for data-driven modeling and simulation and its seamless integration with expert knowledge. The positions are linked to our project ONE4ALL (Horizon Europe 2022), which aims to boost manufacturing plants’ transformation, especially SMEs, towards industry 5.0 (I5.0), reinforcing their resilience under unexpected changes in social needs. Our part in this project is the digital replication of the physical modules and processes through data-driven digital twins and controlled by a self-learning AI-based distributed and multidisciplinary decision support system (DSS). The tasks include: • Gathering data requirements and linking them to objectives • Working on developing an architecture for digital twins of manufacturing systems • Regular communication with project partners and demonstrators (manufacturing facilities) • Implementing a proof of concept for the above tasks • Documenting all tasks and outcomes Qualifications and Skills: We are looking for highly motivated students (Bachelor or Master level) in computer science, industrial engineering, information sciences or similar, preferably at the Karlsruhe Institute of Technology (KIT) • Knowledge and experience in the development of software applications, preferably in Python and/or Java • Basic knowledge of Internet of Things (IoT) devices, Information Extraction and/or Data Science • Experience and knowledge in modeling, simulation, digital twins and manufacturing systems is a plus • Willingness and ability to communicate with project partners of different backgrounds • Sufficient language skills in English to work in an international team We offer: • A contract with 20-80h per month (the salary depends on the university degree). The contract can last between 2 and 6 months. • Flexible working hours, also working at home possible. • A variety of tasks so that you can learn a lot. Also state-of-the-art research can be performed and will be published together with the student. The payment is based on the rates of the state of Baden-Württemberg for academic assistants. The employment is temporary. Please send your application via email to sanja lazarova-molnar∂kit edu using the job posting number "S1".
Forschungsgruppe: Systems, Data, Simulation & Energy (Sanja Lazarova-Molnar)
Beschreibung: Keine Beschreibung verfügbar

Conditions
  • Position: Student Research Assistant (Hiwi)
  • Department: Institute of Applied Informatics and Formal Description Methods
  • Supervisor: Marcus Fechner
  • Location: Karlsruhe Institute of Technology (KIT)


About Us

At the research group “Applied Technical-Cognitive Systems”, we are at the forefront of deep learning in the context of applied machine intelligence. Our research is in the area of autonomous systems, from self-driving cars (CoCar NextGen, CoCar and the shuttles Anna and Ella) to autonomous service robots. We utilize deep learning and other machine learning based approaches to advance these fields.



Position Overview
  • Position: Student Assistant
  • Start Date: As soon as possible
  • Working Hours: 20 - 80 hours per month
  • Duration: 6 months with possibility of extension


Job Description

Developing generally capable reinforcement learning agents poses a significant challenge, especially in hard exploration tasks. Expert robotic data is scarce and expensive, but also reward functions are not easy to design for complex tasks. On the other hand, unlabeled expert video data is abundant, but not straightforward to learn behavioral priors from, as no labels exist (actions).

In this research, we want to investigate how we can train agents on unlabeled expert videos, such as YouTube videos, in a scalable way to master a wide variety of complex tasks, not solvable by conventional reinforcement learning. For support on this topic, we are searching for a motivated student.

Your primary responsibilities will include:

  • Implementing and training deep learning models.
  • Reading related research papers and participating in discussions on the topic.
  • Collaborating with us on experimental design, execution, and evaluation.
  • Other tasks as assigned related to our research.


Qualifications
  • Current enrollment as a student at KIT.
  • Strong interest in deep learning and machine learning.
  • Knowledge of the programming language Python.
  • Knowledge of PyTorch and/or Tensorflow.
  • Experience in working with Linux and Git.
  • Motivated to read research papers.
  • Motivated, responsible, and a quick learner.
  • Speak either German and/or English.


What we Offer
  • Gain hands-on experience in the field of deep learning and conducting systematic research.
  • Work closely with experienced researchers and PhD candidates.
  • Weekly to bi-weekly meetings with supervisor.
  • Coding support and helpful supervision.
  • Flexible working hours to accommodate your class schedule and the option for working remotely.
  • Contribute to research projects and papers.
  • Access to top-of-the-line deep learning workstations with the latest GPUs.


How to Apply

If you are enthusiastic about deep learning and eager to contribute to our research, please send your application to [mailto:marcus fechner∂kit edu marcus fechner∂kit edu] with the following documents:

  1. Cover letter (0.25-0.5 pages): Why do you want to work on this topic? Why are you suitable for the position? (mention your interests and relevant skills).
  2. CV/Resume (max. 2 pages).
  3. Recent transcript of records / grading table.
  4. Optional: Any relevant coding or project portfolio.


If you have any questions or need further information, please contact [mailto:marcus fechner∂kit edu marcus fechner∂kit edu]. Natürlich auch gerne auf Deutsch :)


Forschungsgruppe: Angewandte Technisch-Kognitive Systeme (Marcus Fechner)
Beschreibung: Keine Beschreibung verfügbar

Conditions
  • Position: Student Research Assistant (Hiwi)
  • Department: Institute of Applied Informatics and Formal Description Methods
  • Supervisor: Marcus Fechner
  • Location: Karlsruhe Institute of Technology (KIT)


About Us

At the research group “Applied Technical-Cognitive Systems”, we are at the forefront of deep learning in the context of applied machine intelligence. Our research is in the area of autonomous systems, from self-driving cars (CoCar NextGen, CoCar, and the shuttles Anna and Ella) to autonomous service robots. We utilize deep learning and other machine learning-based approaches to advance these fields.



Position Overview
  • Position: Student Assistant
  • Start Date: As soon as possible
  • Working Hours: 20 - 80 hours per month
  • Duration: 6 months with the possibility of extension


Job Description

Dealing with the real world is challenging, as changing weather conditions, new objects, situations, etc. alter the data observed by the model. In practice, this data distribution shift or out-of-distribution data makes the model unreliable and hinders the safe deployment of deep neural networks in critical use cases, for example, autonomous driving. Models that fail to generalize in such scenarios may result in dangerous or catastrophic behavior.

In this research, we want to investigate how we can integrate different methods to estimate uncertainty in popular object detection models, to reliably detect when the model might fail. For support on this topic, we are searching for a motivated student.

Your primary responsibilities will include:

  • Implementing and training deep learning models.
  • Reading related research papers and participating in discussions on the topic.
  • Collaborating with us on experimental design, execution, and evaluation.
  • Other tasks as assigned related to our research.


Qualifications
  • Current enrollment as a student at KIT.
  • Strong interest in deep learning and machine learning.
  • Knowledge of the programming language Python.
  • Knowledge of PyTorch and/or Tensorflow.
  • Experience in working with Linux and Git.
  • Motivated to read research papers.
  • Motivated, responsible, and a quick learner.
  • Speak either German and/or English.


What we Offer
  • Gain hands-on experience in the field of deep learning and conducting systematic research.
  • Work closely with experienced researchers and PhD candidates.
  • Weekly to bi-weekly meetings with supervisor.
  • Coding support and helpful supervision.
  • Flexible working hours to accommodate your class schedule and the option for working remotely.
  • Contribute to research projects and papers.
  • Access to top-of-the-line deep learning workstations with the latest GPUs.


How to Apply

If you are enthusiastic about deep learning and eager to contribute to our research, please send your application to [mailto:marcus fechner∂kit edu marcus fechner∂kit edu] with the following documents:

  1. Cover letter (0.25-0.5 pages): Why do you want to work on this topic? Why are you suitable for the position? (mention your interests and relevant skills).
  2. CV/Resume (max. 2 pages).
  3. Recent transcript of records / grading table.
  4. Optional: Any relevant coding or project portfolio.


If you have any questions or need further information, please contact [mailto:marcus fechner∂kit edu marcus fechner∂kit edu]. Natürlich auch gerne auf Deutsch :)


Forschungsgruppe: Angewandte Technisch-Kognitive Systeme (Marcus Fechner)
Beschreibung: Keine Beschreibung verfügbar