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CENTER FOR
SCALABLE DATA ANALYTICS
AND ARTIFICIAL INTELLIGENCE

Researchers wanted!

We are looking for research associates for our Dresden location starting at the next possible date with a focus on research and development for Big Data / Data Analytics / AI in various research areas.

The positions are initially limited until December 31, 2022, with an option to extend. The period of employment is governed by Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz-WissZeitVG) and offer the chance to obtain further academic qualification. Balancing family and career is an important issue. The positions are basically suitable for candidates seeking part-time employment. Please note that in your application.

We are looking for applicants for the following research areas:

ScaDS.AI-1
Professional assignment: Chair of Machine Learning for Computer Vision (Prof. Dr. Björn Andres)
Scientific area: Computer Vision
Tasks: Curiosity-driven research of fundamental mathematical optimization problems in the field of large-scale machine learning. Design and analysis of algorithms for solving these problems, exactly or approximatively. Implementation, empirical analysis and comparison of these algorithms with respect to real data. Publication of findings and insights in internationally leading conferences and journals.
Requirements: very good university degree in mathematics or computer science or a related discipline. Comprehensive education in mathematics, especially in discrete mathematics and one area of mathematical optimization (e.g. Mathematical Programming, Convex Optimization). Curiosity and strong interest in rigorous methodological research. Very good programming skills in C++. Very good scientific writing skills in English. (Knowledge of German is not required for this position).

ScaDS.AI-2
Professional assignment: Chair of Didactics of Computer Science (Prof. Dr. Nadine Bergner)
Scientific area: AI-related implication on society
Tasks: The activity comprises scientific research and development work to teach competencies in the fields of big data, data analytics and AI to different target groups (from children, adolescents to adults) in the context of a Living Lab. The research assistant should design, implement and evaluate high-quality teaching formats (in classroom, virtual and blended learning), both technically and didactically. Research is being conducted into how highly complex topics in this specialist field can be made accessible to a broad public, how their social relevance can be highlighted, and how basic understanding in the population can be increased.
Requirements: university degree (M. Sc. or equivalent) in computer science teaching (any type of school and second subject) or alternatively in media informatics or computer science, whereby previous knowledge in the area of didactics or experience in (university) teaching and especially in the creation of digital learning materials is required.

ScaDS.AI-3
Professional assignment: Chair of Adaptive Dynamic Systems (Prof. Dr. Diana Göhringer)
Scientific area: Scalable AI
Tasks: scientific research and development work in the field of big data, data analytics and AI, in particular in the area of design and programming methods for domain specific overlay architectures for FPGA accelerator cards (e.g. Xilinx Alveo); presentation of results at international conferences; participation; close collaboration with academic and industrial cooperation partners.
Requirements: university degree (M. Sc. or equivalent) in computer science, electrical engineering or information technology or in a comparable engineering or natural science; very good knowledge of the programming languages C/C++, high-level synthesis tools/compilers and Field Programmable Gate Arrays; high degree of independence, commitment, flexibility and team spirit; very good knowledge of German and English. Experience in these fields is desirable: Computer architecture, hardware description languages (e.g. VHDL, Verilog) and artificial intelligence.

ScaDS.AI-4
Professional assignment: Chair of Knowledge-Based Systems (Prof. Dr. Markus Krötzsch)
Scientific area: Knowledge-Aware Computing
Tasks: scientific research and development work in the field of artificial intelligence, in particular related to the representation and processing of human knowledge in intelligent systems. Together with other researchers, you will be working on one or several of the following tasks: 

  • Development of new approaches to use and create big knowledge graphs, such as Wikidata, Open Street Maps and Wikimedia Commons
  • Combination of knowledge-based systems with relevant application fields of AI, such as language understanding, software analysis, or planning
  • Implementation of prototypes and their empirical evaluation
  • Publication and presentation of research results at international events

Requirements: very good university degree (M.Sc. or equivalent) in computer science, mathematics or a closely related field. Creativity and eagerness to actively develop and realize own ideas. Proficiency in the area of symbolic AI (ontologies, knowledge graphs, logic programs, planning, etc.) and in the development of software prototypes in common programming languages. For Postdoc candidates: additional significant research contributions in an area with close relation to the topics of the position. Candidates should be independent in organizing their work, keen on working with teams of experts across other projects, and fluent in English, oral and written.

ScaDS.AI-5
Professional assignment: Chair of Religious Education (Protestant) (Prof. Dr. Birte Platow)
Scientific area: AI-related implication on society
Tasks: The focus is on questions of applied ethics arising from current and future possibilities of artificial intelligence and high performance computing/big data. The research associate will investigate interfaces and interactions of humans and artificial intelligence/big data systems. The focus will be on the self- and world views created by this interaction process. These will be interpreted in a practical-theological/religious pedagogical research paradigm and further elaborated in the context of educational-theoretical and practical questions. The aim is to further develop and quantify a preceding qualitative empirical study and to link it to the questions of the overall project in the horizon outlined above. In this context, ethical issues in the area of big data and AI as well as the (especially social) consequences of the application of these technologies are of particular interest. Furthermore, a discursive-interdisciplinary, dialogical connection of the project to the work of the technical sciences and other partners is explicitly desired.
Requirements: relevant university degree in Protestant Theology and proven expertise in the field of religious education studies. In addition, applicants should be recognizably able to conduct interdisciplinary research, have basic knowledge of empirical research, as well as basic knowledge of digital technologies resulting from the spectrum of topics covered by ScaDS.AI. A confident and professional appearance and excellent communication skills (both in German and English) distinguish you just as much as the ability to quickly familiarize yourself with new and unknown topics.

 
ScaDS.AI-6
Professional assignment: Chair of Econometrics and Statistics, esp. in the Transport Sector (Prof. Dr. Ostap Okhrin)
Scientific area: Applied AI
Tasks: scientific research and development work in the field of big data, data analytics and artificial intelligence, in particular development of reinforcement learning algorithms in the area of trajectory planning for autonomously driving vehicles in mixed traffic, such as bicycle traffic, ship traffic, etc. The legal framework (traffic rules, minimum clearances) and physical laws must be considered for each vehicle.
Requirements: university degree (M. Sc. or equivalent) in computer science, mathematics, statistics or a comparable engineering. Knowledge of traffic simulation, traffic modeling or particle modeling is an advantage.

ScaDS.AI-7
Professional assignment: Chair of Scientific Computing for Systems Biology (Prof. Dr. Ivo F. Sbalzarini)
Scientific area: big data, data analytics and AI for the Life Sciences in particular in Systems Biology
Tasks: The Chair of Scientific Computing for Systems Biology and the Center for Systems Biology Dresden seek a motivated individual with strong background in the algorithmic or mathematical foundations of machine learning and AI to extend its research. Areas of particular interest include, but are not limited to:

  • Inference of differential-equation models from biological microscopy videos and applications to image denoising
  • Physics-informed neural networks (PINN) to accelerate numerical simulations of partial differential equations
  • Theory and Mathematics of deep neural nets: high-dimensional approximation theory, stability analysis, preconditioning, etc.
  • Learning and inference using content-adaptive data representations, particularly of light-microscopy images and videos
  • Training methods for supervised learning based on Design Centering

The position is hosted at the Center for Systems Biology Dresden, a center of the Max Planck Society. Collaborations are expected both within TU Dresden, in particular with the DFG Cluster of Excellence “Physics of Life” and its research group for “data-driven simulation” and with the Faculties of Computer Science and Mathematics, as well as with institutions outside the TU Dresden, e.g. the Center for Advanced Systems Understanding (CASUS) and the Max Planck Institute of Molecular Cell Biology and Genetics.
Requirements: university degree (M. Sc. or equivalent) in computer science, mathematics, or a comparable engineering or science discipline; doctorate (Ph.D. or equivalent) in a topic relevant to the call.

ScaDS.AI-8
Professional assignment: Chair of Systematic Theology (Protestant) (Prof. Dr. Christian Schwarke)
Scientific area: AI-related implication on society
Tasks:
identification of ethical horizons that arise in connection with research and development in the field of big data and AI, and with regard to the (especially social) consequences of the application of these technologies. These ethical questions and perspectives are then processed in such a way that the broader social discourse as well as issues arising in the participating disciplines and in the exchange between these communities are adequately addressed. In this context, the conditions under which the ethical questions or problems arise will also be taken into account and traced back to the underlying concepts of man and society that need to be described in the course of this project. In this way, a comprehensive understanding of the effects of big data and AI is to be achieved. The research results are to be made visible and published nationally and internationally.

Requirements: relevant university degree in Protestant Theology as well as an outstanding doctorate in the field of systematic theology/ethics. In addition, knowledge in the field of cultural studies, a recognizable interdisciplinary orientation, as well as an interest in technology and proximity to questions arising from the spectrum of topics covered by ScaDS.AI are expected. A confident and professional appearance as well as excellent communication skills (in both German and English) distinguish you, as does the ability to quickly familiarize yourself with new and unfamiliar topics. Furthermore, experience in project management, in the organization of events, in the management of third-party funds as well as the willingness to get involved in the field of the so-called third mission are desirable.

ScaDS.AI-9, ScaDS.AI-10
Professional assignment: Service Center ScaDS.AI Dresden/Leipzig
Scientific area: Service Center
Tasks: scientific research and development work in the field of big data, data analytics and AI, in particular in close collaboration with partners from applied sciences; Application of methods to support data-intensive scientific workflows, especially on HPC and cluster systems; parallelization and optimization of user workflows and generalization of various big-data analytics strategies or machine learning methods for their application to other subject areas; development and implementation of training measures in these areas.
Requirements: university degree (M. Sc. or equivalent) in computer science, mathematics or a comparable engineering or natural science; high degree of independence, commitment, flexibility and team spirit as well as very good English skills; knowledge in the areas of data analytics, machine learning or scientific computing; experience with HPC systems and/or distributed computing (grid or cloud computing) as well as experience with visualization tools and methods of data mining are desired.

ScaDS.AI-11
Professional assignment: Service Center ScaDS.AI Dresden/Leipzig
Scientific area: Living Lab
Tasks: scientific research and development work in the field of big data, data analytics and AI, in particular in close collaboration with partners from applied sciences; support and further development of demonstrators and prototypical developments for the presentation of methodological solutions in the field of big data, data analytics and AI; development of material and content trainings in various formants, for students as well as scientists
Requirements: university degree (M. Sc. or equivalent) in computer science, mathematics or a comparable engineering or natural science; high degree of independence, commitment, flexibility and team spirit as well as very good English skills; knowledge in the areas of data analytics, machine learning or scientific computing; experience with HPC systems and/or distributed computing (grid or cloud computing) as well as experience with visualization tools and methods of data mining are desired.

 

Applications from women are particularly welcome. The same applies to people with disabilities.

Please submit your comprehensive application with indication of the position (ScaDS.AI-1 to ScaDS.AI-11) including the usual documents by January 7, 2021 (stamped arrival date of the university central mail service applies) to TU Dresden, Zentrum für Informationsdienste und Hochleistungsrechnen, Herrn Prof. Dr. Wolfgang E. Nagel – persönlich -, Helmholtzstr. 10, 01069 Dresden or via the TU Dresden SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf-document to This email address is being protected from spambots. You need JavaScript enabled to view it.. Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.

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Reference to data protection: Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis