Die Stiftung Warentest hat die Poliklinik für Präventive und Rehabilitative Sportmedizin der TU München mit einem Spitzenplatz bewertet. Getestet wurden sportmedizinische Checks in sportmedizinischen Zentren und bei niedergelassenen Ärzten.

Start mit TU Kopenhagen: Allianz für Naturwissenschaft und Technik

Wegen Ausfällen der Datenleitung zum Leibniz-Rechenzentrum nach Garching kann es zu Beeinträchtigungen im Portalbetrieb kommen.

Hilfskraft zur Erstellung von Moodle-Aufgaben für Analysis 3 (EI) gesucht

The Chair of Robotics, Artificial Intelligence and Real-Time Systems offers thesis positions in the area of software development in the automotive context.

Die Geschäftsstelle des TranslaTUM sucht ab sofort eine/n „Controller/in mit IT-Kenntnissen (m/w/d)“ in Voll-zeit (40,1 Wochenstunden)

Das Institut für Anästhesiologie am Deutschen Herzzentrum München des Freistaates Bayern - Klinik an der Technischen Universität München - sucht zum nächstmöglichen Zeitpunkt eine Institutsassistentin/-sekretärin (m/w/x)

Im Präsidium der TUM wird zum 1. September 2021 eine studentische Hilfskraft für ca. 9 Stunden/Woche zur Unterstützung des Büros des Präsidenten bei administrativen und organisatorischen Aufgaben gesucht.

Die Professur für Umweltsensorik und Modellierung bietet eine Master Thesis zur Entwicklung einer Messeinheit mit mehreren Instrumenten, welche auf einer mobilen Plattform integriert wird (Fahrrad, E-Bike, Cargo- Bike, …). Diese dient zur Kalibrierung der Knoten unseres IoT-Sensornetzwerkes zur Luftqualitätsmessung. Mithilfe der Messeinheit wird dann eine Messkampagne in München durchgeführt.

UnternehmerTUM offers founders and startups a complete service from the initial idea to IPO. A team of experienced entrepreneurs, scientists, managers and investors supports founders with the development of their products, services and business models. The experts accompany them actively with building up their companies, market entry and financing - also via the UnternehmerTUM Fund. The accelerator programme TechFounders coaches technology startups over a period of 20 weeks up to an initial venture round, and paves the way for joint ventures with established companies. For industry partners, UnternehmerTUM is a unique platform for cooperation with new companies, and for expansion of their innovative strength and culture. Covering 1500 square metres, 'MakerSpace', Europe's largest publicly accessible high-tech workshop, enables companies, startups and creatives to produce prototypes and small batches using state-of-the-art machines such as large 3D printers. UnternehmerTUM was founded in 2002 by the entrepreneur Susanne Klatten. With more than 50 high-growth technology start-ups each year and its unique offering, it is the leading center for business creation in Germany.

PhD position on: “Real-Time resource control for heterogeneous multicore SoC” Brief Info: • Laboratory: Chair of Cyber Physical Systems in Production Engineering, Technical University of Munich. (See http://www.professoren.tum.de/caccamo-marco/ ) • Supervisors: Marco Caccamo, Luca Abeni • We are currently looking for motivated Ph.D. students who would like to work at TUM, Munich in collaboration with Scuola Superiore S’Anna, Pisa • Contacts: email mcaccamo@tum.de and luca.abeni@santannapisa.it Scientific Context Modern heterogeneous multi-core System-on-Chip (SoC) technologies in embedded computing systems pose new challenges for safety critical and real-time applications due to (i) increased temporal coupling between processing cores, (ii) higher degree of software integration and (iii) increased uncertainty in the hardware timing model that is used in the development and certification of embedded software for safety critical real-time systems (like avionics, autonomous automotive systems, production robots, etc.). In multicore architectures, coupling across distinct software partitions arises because of shared hardware resources (like cache, main memory, I/O, and dedicated hardware engines), and result in loss of composability. In other words, when two software components are composed (i.e., simultaneously executed), the effect that one has on the performance of another can be significant, resulting in unexpected temporal behavior. The problem of inter-core performance interference in multicore architectures is well known and has been largely studied in literature [1, 2]; additionally, last generation architectures include several heterogeneous hardware components including programmable logic (PL), graphics processing units (GPUs), vision processing units (VPUs), tensor processing units (TPUs) to name a few. These complex heterogeneous platforms have further aggravated the inter-core interference problem [3] but they also provide a unique opportunity for us to invent near-optimum integrated hardware-software real-time resource management primitives. Research The PhD candidate will review the existing literature on the broad topic of resource management for realtime heterogeneous SoCs, identify a specific problem (or a set of problems) he/she plan to solve, and then research, develop, and evaluate innovative resource management solutions to address the highlighted issue(s). To do this, the candidate will focus his/her attention on a specific sub-system of these complex architectures based on the preference/skills of the student and recommendations by the supervisors. Requirements The candidate is required to have a Master degree in computer science or electrical computer engineering and preferably should have a strong background in computer architecture, real-time systems theory, and operating systems; but at least in two of those listed fields. [1] H. Kim, D. de Niz, B. Andersson, M. Klein, O. Mutlu, and R. Rajkumar. Bounding memory interference delay in cots-based multi-core systems. In 2014 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS), pages 145–154, April 2014. [2] L. Sha, M. Caccamo, R. Mancuso, J.-E. Kim, M.-K. Yoon, R. Pellizzoni, H. Yun, R. Kegley, D. Perlman, G. Arundale and R. Bradford, "Real-Time Computing on Multicore Processors", IEEE Computer, Vol. 49, Issue 9, pp. 69-77, September 2016. [3] M. Yang, N. Otterness, T. Amert, J. Bakita, J. Anderson, and F. D. Smith, “Avoiding Pitfalls when Using NVIDIA GPUs for Real-Time Tasks in Autonomous Systems”, Proceedings of the 30th Euromicro Conference on Real-Time Systems, pp. 20:1-20:21, July 2018

After just two years in orbit, ESA's GOCE satellite has gathered enough data to map Earth's gravity with unrivalled precision. In a project coordinated by researchers from Technische Universitaet Muenchen (TUM), scientists have now produced the most accurate model of the global gravitational field ever produced to further our understanding of how Earth works. It was unveiled today at the Fourth International GOCE User Workshop at TUM.

Datum / date: 28.04.2011 Treffpunkt / meeting point: Marienplatz/Mariensäule Uhrzeit / time: 13.00 Uhr Kosten / costs: 3 Euro Max. Teilnehmerzahl / max number of participants: 30 Anmeldung / registration: Online mit Bezahlung im TUMi Büro / online with payment in TUMi office Tutoren / tutors: Sebastian P., Krasi, Andi

Der Exzellenzcluster ORIGINS ist ein interdisziplinärer Forschungsverbund, an dem Forscher verschiedenster Institutionen im Münchner Raum beteiligt sind. Die Wissenschaftler untersuchen die Entwicklung des Universums vom Urknall bis zur Entstehung des Lebens und verknüpfen dazu auf einzigartige Weise die Fachrichtungen Astrophysik, Biophysik und Teilchenphysik. Die Geschäftsstelle des Clusters ORIGINS sucht zum nächstmöglichen Zeitpunkt eine

Modern computer-assisted surgery relies increasingly on robust visual understanding of the operating room. While most existing approaches for surgical scene understanding and phase recognition are based on narrow-field-of-view endoscopic or monocular camera data, real-world operating rooms often provide significantly richer visual contexts. This thesis aims to investigate surgical scene understanding using multiple images for surgical phase recognition, and higher-level scene representations such as surgical scene graphs. The goal is to analyze how VLM/multi-view VLMs can use the visual context can improve robustness, generalization, and interpretability. The project will commence with a comprehensive review of the state-of-the-art in surgical activity recognition, surgical phase classification, and scene graph–based modeling. Based on this review, existing methods will be categorized and experimentally evaluated, with adaptations made where necessary to support panoramic or wide-field-of-view imagery. Particular emphasis will be placed on testing and validating approaches on recordings beyond classic benchmark datasets, including less constrained or previously unseen surgical recordings. The student is encouraged to bring in their own ideas and creativity. The outlined approach serves as a guiding framework rather than a strict implementation plan. Your own creativity is welcome to solve the problem; the upper proposal merely presents an idea. Please read the application details: https://hex-lab.io/vacancies/01_students/ Key research areas include: Reviewing the state-of-the-art in surgical activity / phase classification techniques and surgical scene graph techniques Categorize and experiment with existing approaches Test on recordings aside from classic datasets Recommended background (or motivation in learning): Basic knowledge of computer vision Experience with deep learning model training and application Some experience with C++ and Python Medical Context: - https://github.com/egeozsoy/ORacle Multi-View VLMs: - InternVL https://github.com/OpenGVLab/InternVL - LLaVA-NeXT as well: https://arxiv.org/abs/2407.07895; https://github.com/LLaVA-VL/LLaVA-NeXT Fine-tuning VLMs for 3D vision tasks: - https://github.com/openvla/openvla - https://roboflamingo.github.io/ - https://physx-anything.github.io/