
Want to be part of transforming road freight – for good? Einride is showing the world a new way to move, based on the latest digital, electric and autonomous technologies. Through freight capacity as a service, we enable businesses around the world to accelerate towards their sustainability goals.
Founded in 2016, Einride became the first company in the world to deploy a cab-less autonomous electric vehicle on a public road (Sweden, 2019). In 2022, we were the first to successfully operate such a vehicle on a US public road. Today our award-winning technology has been launched across 8 countries (and counting). Our clients are some of the world’s biggest shippers, including Fortune 500 companies. We are also operating Sweden’s largest truck dedicated public charging network and counting.
We are looking for a highly motivated Industrial PhD candidate to bridge the gap between cutting-edge academic research and industrial application. In this role, you will be employed by Einride Autonomous Technologies while being enrolled as a PhD candidate at University of Gothenburg.
Your research will focus on exploring and devising methodologies to establish Foundation Models as experienced co-workers to evaluate and improve the safety of autonomous systems – during development and in operation.
This is a full-time remote position based in Gothenburg. You will be part of a truly diverse, high performing team with a common passion for sustainability and making things happen in an innovative way. We recommend that you submit your application as soon as possible since selection and interviews are held continually.
Please note that as part of our standard recruitment process, we conduct a background control on the final candidate for this role. This may include verification of education, employment history, any relevant professional certifications or other information that may be of our interest.
At Einride, we are innovators, building solutions the world has never seen before – but urgently needs. That’s why we take action, and it’s why we are always eager to be challenged. We know that our best innovations come from having a diverse mix of people, including those of different experiences, career paths, and walks of life. By coming together and sharing our perspectives openly – by disagreeing, discussing, and committing – we deliver greater impact.
About Chalmers University of Technology:
The Department of Computer Science and Engineering at University of Gothenburg and Chalmers University of Technology in Sweden with approximately 270 employees from more than 30 countries is widely recognized for excellent research and education. The department is located in Sweden’s second largest city Gothenburg – the world’s most sustainable destination every year since 2016 according to the Global Destination Sustainability Index. The research divisions at the department are essential scientific facilitators in a vibrant ecosystem of software-intensive companies such as Volvo, Ericsson, and Einride. This ecosystem is complemented by a growing start-up scene supported by collaboration hubs like MobilityX Labs and AI Sweden, the national center for applied AI that is bringing together over 120 partners across public and private sectors including academia.
The academic host division provides world-leading research and education in the development of complex and software-intense systems and is characterized by extensive international cooperation as well as close collaboration with the local industry. With approximately 50 researchers including PhD students, PostDocs, and professors, we are one of the largest academic software engineering research groups in the world. The core expertise is in AI Engineering (both AI for SE and SE for AI), software testing, requirements engineering, behavioral software engineering, and software engineering for automotive systems. Being broadly recognized in the academic community, the division has hosted top international conferences such as ICSE, SPLC, ICSA, REFSQ, and EASE during the past years.
Job assignments:
Third-cycle studies are equivalent to four years full-time and with the goal to qualify for a Degree of Doctor. Those appointed to doctoral studentships shall primarily devote themselves to their doctoral education. Those appointed to doctoral studentships may, however, work to a limited extent with educational tasks, research and administration, so-called departmental service in a teaching or supporting role, which can be concentrated on certain parts of the year depending on the needs of the business in consultation with the student.
The purpose of the education is for the doctoral student to acquire the knowledge and skills required to be able to conduct independent research in the field of service, and to contribute to the development of knowledge in the subject by writing a scientific dissertation. In addition, the student must meet formal educational criteria such as completing the required amount of higher education credits in courses.
The successful applicant will conduct research under the supervision of Professor Christian Berger in the research project EASe - Evaluate Autonomous Systems with Foundation Models funded by the Swedish Strategic Foundation (SSF).
Eligibility:
To be eligible for third-cycle studies, the applicant must meet both the general and, where applicable, specific entry requirements.
A person meets the general entry requirements for third-cycle studies if they:
1. has been awarded a second-cycle qualification
2. has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second-cycle, or
3. has acquired substantially equivalent knowledge in some other way in Sweden or abroad
You are highly motivated, self-propelled, energetic, independent and with a well-developed analytical problem-solving ability. As a person, you are empathetic, loyal and have high ethical standards.
Assessment:
In selecting between applicants who meet the general and, where applicable specific entry requirements, their ability to benefit from third-cycle studies shall be taken into account.
The ability to work in a team as well as to systematically work within a project environment and its deadlines is desirable.
Documented experience of designing, implementing, testing, and improving machine learning (ML)-based software with state-of-the-art tools (eg., Linux, Docker, Python, PyTorch, TensorFlow, and OpenCV) is considered a merit.
Born autonomous. Born electric.
Since 2016, our technology has connected global communities with the things they need – and all without the emissions. We’re made up of experts in multiple fields and that’s how we’ve developed a new way to move goods. This is technology purpose-built for the industry. This is safer, cleaner, and more reliable movement.
We are Einride and this is how we build a better future.