We combine deep expertise in protein science with modern AI-driven methods to design and optimize next-generation protein therapeutics. * Apply AI-driven protein engineering methods to support protein design projects * Apply physics-based modelling approaches (Rosetta/PyRosetta) together with cutting-edge generative AI methods, protein language models (PLMs), and structure prediction technologies to drive protein design, optimization and engineering efforts * Strong Python programming and scripting skills, including development of analysis workflows and computational pipelines * Curiosity about advances in generative AI, with the ability to rapidly learn and apply new methods to protein engineering projects in a fast-paced research environment
We combine deep expertise in protein science with modern AI-driven methods to design and optimize next-generation protein therapeutics. * Apply AI-driven protein engineering methods to support protein design projects * Apply physics-based modelling approaches (Rosetta/PyRosetta) together with cutting-edge generative AI methods, protein language models (PLMs), and structure prediction technologies to drive protein design, optimization and engineering efforts * Strong Python programming and scripting skills, including development of analysis workflows and computational pipelines * Curiosity about advances in generative AI, with the ability to rapidly learn and apply new methods to protein engineering projects in a fast-paced research environment
The Junior Research Group Digital Collectomics deals with the development of automated methods revolving around the extraction of information from collections, with a strong focus on herbaria, as well as the digitization process and public display thereof. We leverage the latest developments in computer vision and AI research to create broadly applicable methods that can deal with small to no available training data. Therefore, our research focuses primarily on foundation models, few- and zero-shot methods and domain generalization. In interdisciplinary cooperation with the local Herbarium Haussknecht and other partners all over Senckenberg, we create cutting-edge approaches for publication in high-ranked computer vision, machine learning and interdisciplinary venues with the ambition to convert the novel methods into directly applicable tools usable in ...
The Junior Research Group Digital Collectomics deals with the development of automated methods revolving around the extraction of information from collections, with a strong focus on herbaria, as well as the digitization process and public display thereof. We leverage the latest developments in computer vision and AI research to create broadly applicable methods that can deal with small to no available training data. Therefore, our research focuses primarily on foundation models, few- and zero-shot methods and domain generalization. In interdisciplinary cooperation with the local Herbarium Haussknecht and other partners all over Senckenberg, we create cutting-edge approaches for publication in high-ranked computer vision, machine learning and interdisciplinary venues with the ambition to convert the novel methods into directly applicable tools usable in ...
The Junior Research Group Digital Collectomics deals with the development of automated methods revolving around the extraction of information from collections, with a strong focus on herbaria, as well as the digitization process and public display thereof. We leverage the latest developments in computer vision and AI research to create broadly applicable methods that can deal with small to no available training data. Therefore, our research focuses primarily on foundation models, few- and zero-shot methods and domain generalization. In interdisciplinary cooperation with the local Herbarium Haussknecht and partners all over Senckenberg, we create cutting-edge approaches for publication in high-ranked computer vision, machine learning and interdisciplinary venues with the ambition to convert the novel methods into directly applicable tools usable in ...
The Junior Research Group Digital Collectomics deals with the development of automated methods revolving around the extraction of information from collections, with a strong focus on herbaria, as well as the digitization process and public display thereof. We leverage the latest developments in computer vision and AI research to create broadly applicable methods that can deal with small to no available training data. Therefore, our research focuses primarily on foundation models, few- and zero-shot methods and domain generalization. In interdisciplinary cooperation with the local Herbarium Haussknecht and partners all over Senckenberg, we create cutting-edge approaches for publication in high-ranked computer vision, machine learning and interdisciplinary venues with the ambition to convert the novel methods into directly applicable tools usable in ...
You will explore and implement LLM‑based methods and agentic AI approaches to enhance automation, decision support and model interpretability in real retail scenarios.
You will explore and implement LLM‑based methods and agentic AI approaches to enhance automation, decision support and model interpretability in real retail scenarios.
Planning, leading, coordinating improvement initiatives using Lean, Six Sigma, and Kaizen methods to achieve the objectives * Coaching and enabling all employees in Lean methods
Planning, leading, coordinating improvement initiatives using Lean, Six Sigma, and Kaizen methods to achieve the objectives * Coaching and enabling all employees in Lean methods
Technische Tiefe: Fundierte Kenntnisse in SAP ABAP/ABAP OO, SAP Fiori, Fiori Elements, Core Data Services, OData und dem ABAP RESTful Application Programming Model (RAP) setzt du zielgerichtet für maßgeschneiderte Defense-Lösungen ein.
Technische Tiefe: Fundierte Kenntnisse in SAP ABAP/ABAP OO, SAP Fiori, Fiori Elements, Core Data Services, OData und dem ABAP RESTful Application Programming Model (RAP) setzt du zielgerichtet für maßgeschneiderte Defense-Lösungen ein.