Jobs

Chair for Software for Systems on Silicon

  • RWTH Aachen University is Germany´s top-ranked technical university with approx. 45,000 students. The Institute for Communication Technologies and Embedded Systems (ICE) is headed by Prof. Rainer Leupers and Prof. Dr. Haris Gačanin. ICE performs R&D projects in different areas of embedded and cyber-physical system design. Our main application domains are mobile communications, automotive…

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Chair for Distributed Signal Processing

  • There are different opportunities for excellent postdoctoral researchers, which are hired and compensated as full-time researchers, at the Chair for Distributed Signal Processing (Prof. Dr. Haris Gačanin, www.dsp.rwth-aachen.de) of RWTH Aachen University in Aachen, Germany. Current positions are part of efforts toward the development of 6G radio access technologies and laboratory in the…

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  • There are multiple vacancies for excellent Ph.D. candidates, which are hired and compensated as full-time researchers, at the Chair for Distributed Signal Processing (Prof. Dr. Haris Gačanin, www.dsp.rwth-aachen.de) of RWTH Aachen University in Aachen, Germany. Current positions are part of efforts toward the development of 6G radio access technologies and laboratory in the intersection of digital…

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HiWi / WiHi job offers

  • Abstract TLM-based Model for on-Chip Interconnects

    Supervisor: Dr.-Ing. Jan Moritz Joseph
    Description: Using exsiting low-level models for on-chip interconnects, higher-level models can be deduced. Here, we will use our existing ratatoskr open-source simulator on cycle-accurate abstraction level to model the interconnect on a transaction-level model (TLM) accouting for the network topology and the network congestion. Performance and power are to be estimated.

  • Hardware-Security: IP Integrity Protection

    Description: Here at the Chair for Software for Systems on Silicon (SSS), we are looking into novel ways of securing hardware designs (in particular processor cores) against hardware Trojans, taking the complexity of modern circuits into account.
    Supervisor: Dominik Šišejković

  • Hardware Security: Secure Processor Design

    Supervisor: Lennart Reimann
    Description: In this work we would like to address the development and evaluation of tools to elaborate and/or quantify the security properties of a processor design. The properties Confidentiality, Integrity (, Availability) and Authenticity (CI[A]A) need to be protected.

  • High-performance FPGA-based NoC Co-Emulation-Simulation Framework for HW-Security Evaluation

    Supervisor: Dr.-Ing. Jan Moritz Joseph
    Description: The goal of this thesis is to extend a the aforementioned framework by a new in-house NoC model. Furthermore, a experiemental setup to assess the NoC's side channels must be implemented (including measurements in the lab).

  • HiWi job offer - Pluto and webportal exercise

    Description: We introduce an interactive learning portal to complement teaching with combination of software and hardware exercises. We defined computer simulation exercises and educational software-defined radio (SDR) platform where baseband functions are implemented in SDR to experience a real-life communication over a wireless channel. The simulations and the hands-on exercises seamlessly merge through reuse of essentially the same C language-based code. The major goals are as follows:
    • Provide interactive web-based platform for the students to remotely, at time of their choice, and with maximum flexibility in execution simulate theoretic concepts covered in class.
    • Provide state-of-the-art hands-on experience to the students with the specified software defined radio. Students can implement, try, and manipulate the code running on the software radio to develop deep understanding of the theoretic concepts learned in class.

    Supervisor: Dr. H. Kremo

  • Machine Learning for Security

    Description: In the context of this work, we will address some selected challenges from the area of hardware security by applying modern machine learning techniques.
    Supervisor: Dominik Šišejković

  • Neuroflow: SW/HW-Interfaces for Neuromorphic Computing

    Supervisor: Felix Staudigl
    Description: In the context of this work, we will invent a novel way of computation in neuromorphic devices. These problems are closely related to existing soltions for Google's TPU-style way of data processing. Their approaches must be translated into the neuromorphic world.

  • Neuromorphic Hardware Security

    Supervisor: Felix Staudigl
    Description: This Master/Bachelor Thesis aims to investigate novel Hardware Security vulnerabilities and their countermeasure of neuromorphic computing architecture. In particular, the student will have the unique opportunity to work with the real ReRAM crossbars to perform measurements within our labs.

  • Neuromorphic Virtual Platforms

    Supervisor: Felix Staudigl
    Description: This Master/Bachelor Thesis aims to develop a virtual prototype to perform a system exploration concerning parameters like power consumption and performance. The virtual prototype will be implemented in C++ together with SystemC/TLM.

  • RISCV plus TensorFlowLite Hardware Platform

    Supervisor: PhD-Ing. Melvin Galicia
    Description: RISCV processors have gained a good level of maturity in the academia and they are trying to breakthrough in the industry. Attaching  RISCV processors to booming commercial technologies like maching learning software is a very promising idea. The job is to bring to life a realization of a platform, where TensorFlow-Lite framework can be compiled and run in an actual RISCV processor.

  • Tackling Avalanches in Spiking Neural Network Accelerators

    Description: In this master thesis, a standard spiking neural network is trained using Tensorflow. The avalanches are shown by means of software. Next, the amount and timing of avalanches are modeled mathematically. Furthermore, the software model is attached to a SystemC model of the on-chip network. The performance impact of avalanches is quantified. Finally, an architectural optimization is proposed to overcome performance limitations. 
    Supervisor: Dr.-Ing. Jan Moritz Joseph

  • We are hiring! Programmers (C++, Python), Data Scientists, Hardware Engineers

    Description: There is plenty of work in our team. Developing hardware, building prototypes, maintaining open-source software, or inventing new ML models? That’s all possible! We will find a task that fits your profile best.

  • Wi-Hi Position: Programming

    Description: The ICE is looking for a Bachelor graduate who will be employed for software development as a half-time scientific assistant (WiHi, 20h per week).
    Tutor: Shawan Mohammed

Neuroflow: SW/HW-Interfaces for Neuromorphic Computing:

Background:

Machine  learning,  big-data  and  internet-of-things are  some  of  the  emerging  computing  applications  which  are extremely  demanding  in  terms  of  storage,  energy  and  performance. While conventional von Neumann architectures are facing significant challenges to cope with such demands, computing-in-memory  architectures  in  general  and  neuro-inspired  architectures, in  particular, represent a  promising  solution  to  overcome these  limitations. This Master Thesis aims to tackle the Software-Hardware interface of novel neuro-inspired accelerators by investigating the mapping and scheduling of state-of-the-art workloads onto memristor-based systolic areas.

Supervisor:

Felix Staudigl

Requirements:

You will need to have...

  • ... an interest in modelling
  • ... good knowledge of C++ and Python.
In case of interest, please send me an email including the following:
  • Very short motivational letter (4-6 sentences)
  • Latest transcript of records
  • A brief description of your background and CV (if available)

Description:

In the context of this work, we will invent a novel way of computation in neuromorphic devices. These problems are closely related to existing soltions for Google's TPU-style way of data processing. Their approaches must be translated into the neuromorphic world.

Tasks:

Amoung others, these step must be done:

  • Characterize neuromophic processing devices
  • Implement neuromorphic extension for Tensorflow
  • Formulate optimization problems for mapping of compute
  • Propose a neuromorphic mapping and scheduling tool chain
  • Evaluation and verification by means of simulation