Big part of our success is owed to developing young talents and supporting your growth with our know-how. And it's not a one-way street. We learn a lot from you and your ability to see things from a different angle. Together we are better!
Please find our open internships on our job openings page here.
Upcoming job fairs or events
Please look up if we soon have a job fair or an event (face to face or virtual). Come and exchange with us to learn more about u-blox and its opportunities: upcoming events.
u-blox (SIX:UBXN) is a global provider of leading positioning and wireless communication technologies for the automotive, industrial, and consumer markets. Their solutions let people, vehicles, and machines determine their precise position and communicate wirelessly over cellular and short-range radio networks.
With a broad portfolio of chips, modules, and a growing ecosystem of products supporting data services, u-blox is uniquely positioned to empower its customers to develop innovative solutions for the Internet of Things, quickly and cost effectively. With headquarters in Thalwil, Switzerland, the company is globally present with offices in Europe, Asia, and the USA.
Project 1: System in Package (SiP) with embedded antenna
Small size and low power consumption are essential for IoT modules based on Bluetooth, Wi-Fi and/or UWB wireless technologies. It is possible to use system-in-package modules, where separate chips and antenna(s) are embedded and connected individually with the target to reduce the module size. This thesis will evaluate SiP solutions and focus on the performance and size when one or two antennas are embedded in the package.
The antenna performance is dependent on its size and structure as well as on the layout of the ground plane and objects in the vicinity of the antenna. It is important to consider both how the embedded antenna is placed in the SiP module and how the module is placed on the carrier board, providing large bandwidth and good radiation characteristics.
The goal of this topic is to study different SIP concepts with embedded antenna(s). The focus is to compare the SiP and antenna performance for extended bandwidth covering Wi-Fi and UWB in the frequency range from 5 GHz to 9 GHz. The thesis work will include technical studies, design proposals, simulations and measurements of antenna prototypes. The analysis and documentation of simulation results and measurement data of prototype performance will be included in the thesis studies.
- Familiar with HW design and Wi-Fi/UWB chips
- Background on RF and antenna design
- Good knowledge of RF simulation tools (e.g. HFSS)
We think this can be done by 1-2 persons in the Malmö or Berlin office.
To apply, contact email@example.com or firstname.lastname@example.org
Project 2: Hybrid wireless positioning
There is an increasing interest in tracking and navigation applications based on positioning in a seamless manner between and within indoor and outdoor environments. Seamless positioning methods and fusion of inputs from different wireless technologies and sensors enable the universal positioning use cases and can enhance the localization accuracy.
The topics to be investigated in this thesis work include methods and fusion algorithms of GNSS and short-range wireless technologies for seamless indoor and outdoor positioning. The study will focus on seamless fusion of positioning data from Bluetooth direction finding and GNSS receivers. The fusion algorithms in the core positioning engine will be evaluated for network-based tracking use cases. The study will evaluate fusion of hybrid positioning signals from wireless technologies based on signal processing and improvements with AI and machine learning inference models.
Specific tasks in the thesis
- Analysis of data from indoor and outdoor system
- Evaluation of sensor fusion algorithms
- Description and comparisons of hybrid positioning performance
- Background in wireless positioning technologies
- Good knowledge in signal processing with matlab tools
- Familiar with machine learning and inference models
This thesis work can be done by 1-2 persons in the Malmö or Athens office.
To apply, contact email@example.com
Project 3: Joint Bluetooth direction finding and distance estimation
Bluetooth is an efficient and low power technology for connectivity and indoor positioning. There is recent progress in the Bluetooth standardization for direction finding and channel sounding estimation technologies. The direction finding enables angle of arrival (AoA) estimations and the channels sounding enables distance estimations.
The topic of this thesis is to evaluate combinations of Bluetooth AoA and distance estimation techniques for enhanced positioning accuracy and new use cases. The joint positioning algorithm will be based on simultaneous or sequential inputs of AoA and distance estimations. The algorithm will be evaluated in Matlab with the target to be embedded in wireless MCU modules. The thesis work will focus on how accuracy can be enhanced with sophisticated joint algorithms and localization techniques.
- Background in digital communications and wireless short range radio technologies
- Familiar with digital signal processing techniques
- Knowledge of wireless positioning methods (angle-of-arrival (AoA), round-trip time (RTT))
- Good knowledge of software programming in Matlab and C
The work can be done by 1-2 persons, in the Malmö or Berlin office.
To apply, contact firstname.lastname@example.org or email@example.com.
Project 4: Next Generation Wi-Fi connectivity and positioning
The aim of this thesis is to study next generation wireless techniques based on recent advancements of Wi-Fi technology (e.g., IEEE 802.11ax, 802.11az, 802.11be, 802.11bf) that make use of higher frequencies and much large bandwidths to advance connectivity.
With these enablers, the position estimation accuracy can be enhanced when combined with sophisticated algorithms and localization techniques.
- Strong background in digital communications and wireless air interfaces (e.g. Wi-Fi, BLE)
- Familiar with digital receiver design and signal processing techniques
- Knowledge of wireless positioning methods (e.g. trilateration, angle-of-arrival (AoA), round-trip time (RTT))
- Very good knowledge of software programming in Matlab (preferably), C or Python
The work can be done by 1-2 persons in the Malmö or Athens office.
To apply, contact firstname.lastname@example.org or email@example.com
Project 5: IoT modules with embedded machine learning inference
There is a growing interest in tiny and embedded machine learning inference models for IoT applications. One typical use case is the reception and transmission of sensor data based on Thread and Wi-Fi protocols. Native IP is fully supported in both Thread and Wi-Fi, where IPv6 provides the space needed for directly addressing all IoT nodes and devices.
This thesis will investigate embedded machine learning models and inference for energy optimized IoT protocols and transmission schemes. The study will analyze how data communication intervals, packet sizes and real time requirements impact the energy consumption among network nodes. The study will focus on finding features and use machine learning (ML) in addition to the standardized PHY and MAC protocols. The goal is to have a compact ML model and embedded inference of sensor data schemes for low energy consumption and sustainable IoT modules.
- Background in wireless digital communications (Wi-Fi, Thread)
- Familiar with digital signal processing techniques
- Knowledge of machine learning tools
- Very good knowledge of software C and Python
The work can be done by 1-2 persons in the Malmö office.
To apply, contact firstname.lastname@example.org
Project 6: Enhanced security and intrusion detection in IoT modules with embedded machine learning inference models
There are growing needs and requests for using wireless IoT modules for a wide variety of applications in industrial and consumer segments. The wireless IoT modules and connectivity between different nodes must be robust and secure.
This thesis will investigate how embedded machine learning models can be used to detect and mitigate anomalies in an IoT module and in a network topology of several nodes. The study will evaluate protocol stacks and data collected from nodes based on IoT modules in a larger network. The study will compare features and use machine learning (ML) based on collected data to investigate if anomalies and/or intrusion can be detected. The goal is to have a compact embedded ML model capable of real time inference of anomaly and intrusion in constrained Wi-Fi, Thread and Bluetooth IoT modules.
- Background in wireless digital communications (Wi-Fi, Bluetooth)
- Familiar with security and privacy
- Very good knowledge of machine learning tools
- Capable of coding and software tools in C and Python
The work can be done by 1-2 persons in the Malmö or Berlin office.
Indoor positioning, embedded ML.
To apply, contact email@example.com or firstname.lastname@example.org
Read what our former interns say about their experience at u-blox