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Postdoctoral Researcher in SDVs and Contextual Observability

We are seeking a highly motivated postdoctoral researcher to join a new project funded by the Interdisciplinary Research Center for Smart Mobility and Logistics. This position offers a unique opportunity to contribute to cutting-edge advancements in software-defined vehicles (SDVs), software observability, data analytics, causal inference, and system resilience.

Key responsibilities

• Develop and implement a testbed for contextual observability, using open-source tools to collect and analyze multimodal telemetry data from SDVs.
• Design and evaluate techniques for real-time fault detection, anomaly identification, and trend analysis.
• Conduct research in causal inference to recognize the root causes of identified anomalies.
• Explore and prototype automated incident response systems for real-time troubleshooting in SDVs.
• Publish high-impact research findings in leading journals and present results at international conferences.

Required qualifications

• PhD in computer science or engineering, systems engineering, or a related field, with expertise in one or more of: software-defined systems, cyber-physical systems, software observability.
• A solid understanding of existing and emerging machine learning techniques.
• Proficiency in programming languages such as Python and C++, preferably both.
• Strong analytical and problem-solving skills, with experience in data collection and analysis from complex systems.
• Excellent communication and interpersonal skills.
• Demonstrated ability to conduct independent research and collaborate within multidisciplinary teams.

Preferred qualifications

• Familiarity with service-oriented and microservice architectures.
• Expertise in data serialization languages such as YAML, JSON, and Protobuf, as well as data distribution and messaging protocols such as MQTT and Zenoh.
• Expertise in API protocols such as REST, GraphQL, WebSocket, and gRPC, along with query languages such as SQL, KQL, PromQL, and LogQL.
• Knowledge of causal modeling.

What we offer

• Competitive salary and benefits package. More information is available here.
• Opportunities to engage with leading experts in smart mobility and logistics.

PhD Student in SDVs and Contextual Observability

We are seeking a dedicated PhD student to contribute to advancing the technological foundation for software-defined vehicles (SDVs). The research will be conducted at KFUPM’s Interdisciplinary Research Center for Smart Mobility and Logistics (SML), focusing on causal inference for SDVs.

Key responsibilities

• Develop and refine a testbed for contextual observability, using open-source tools to collect and analyze multimodal telemetry data.
• Conduct in-depth studies on causal inference to evaluate the effects of software updates, environmental variations, and network conditions on SDVs.
• Present findings at international conferences and publish in peer-reviewed journals.

Required qualifications

• Bachelor's or master's degree in computer science or engineering, systems engineering, or a related field.
• Background in AI, machine learning, and causal inference.
• Proficiency in programming languages such as Python and C++, preferably both.
• Demonstrated ability to undertake independent research and solve complex problems.

Preferred qualifications

• Familiarity with DevOps, OpenTelemetry, and observability frameworks.
• Expertise in data serialization languages such as YAML, JSON, and Protobuf, as well as data distribution and messaging protocols such as MQTT and Zenoh.
• Expertise in API protocols such as REST, GraphQL, WebSocket, and gRPC, along with query languages such as SQL, KQL, PromQL, and LogQL.
• Interest in real-time systems and connected vehicle technologies.

MSc Student in SDVs and Contextual Observability

We are looking for a motivated MSc student to participate in cutting-edge research on software-defined vehicles (SDVs). This position offers an opportunity to contribute to advances in observability, data analytics, and system resilience for SDVs.

Key responsibilities

• Assist in the development and validation of a testbed for contextual observability in SDVs.
• Conduct experiments to collect and analyze telemetry data for real-time system monitoring.
• Explore anomaly detection techniques and resource optimization methods for SDVs.
• Publish research findings in leading journals and present results at international conferences.

Required qualifications

• Bachelor's degree in computer science or engineering, systems engineering, or a related field.
• Proficiency in programming languages such as Python and C++, preferably both.
• Basic knowledge of artificial intelligence, machine learning, or data analytics.
• Strong problem-solving skills and a passion for research.

Preferred qualifications

• Familiarity with DevOps, OpenTelemetry, and observability frameworks.
• Expertise in data serialization languages such as YAML, JSON, and Protobuf, as well as data distribution and messaging protocols such as MQTT and Zenoh.
• Expertise in API protocols such as REST, GraphQL, WebSocket, and gRPC, along with query languages such as SQL, KQL, PromQL, and LogQL.
• Interest in real-time systems and connected vehicle technologies.

Postdoctoral Researcher in Seamless Integrated Mobility

We are seeking a highly motivated postdoctoral researcher to lead cutting-edge research on developing an AI-based framework for Seamless Integrated Mobility (SIM). This project focuses on creating an inclusive and unified mobility platform that integrates multimodal transportation options while addressing the diverse needs of all citizens, including individuals with disabilities, the elderly, and low-income groups.

Key responsibilities

• Lead the design and implementation of AI agents for specific mobility functions such as trip planning, service bundling, demand-supply matching, and user profiling.
• Conduct comprehensive stakeholder analyses to identify key players in Saudi Arabia's mobility ecosystem and assess current urban mobility challenges.
• Develop detailed user personas and use them to inform the design and deployment of the SIM platform.
• Prototype and test the SIM platform using real-time data, ensuring adaptability to evolving user needs.
• Publish high-impact research findings in leading journals and present results at international conferences.

Required qualifications

• PhD in computer science or engineering, AI, transportation engineering, or a related field.
• Strong expertise in AI, machine learning, and service-oriented architectures.
• Proficiency in programming languages such as Python and C++, preferably both.
• Experience in developing and deploying agent-based systems.
• Demonstrated ability to conduct independent research and lead complex projects.

Preferred qualifications

• Knowledge of multimodal transportation systems or smart mobility frameworks.
• Familiarity with user-centered design methods, including persona development.
• Background in urban mobility challenges and solutions.
• Expertise in data serialization languages such as YAML, JSON, and Protobuf, as well as data distribution and messaging protocols such as MQTT and Zenoh.
• Expertise in API protocols such as REST, GraphQL, WebSocket, and gRPC, along with query languages such as SQL, KQL, PromQL, and LogQL.

What we offer

• Competitive salary and benefits package. More information is available here.
• Opportunities for interdisciplinary collaboration and engagement with key stakeholders in the mobility sector.

PhD Student in Seamless Integrated Mobility

We are looking for a dedicated PhD student to contribute to the development of an AI-based framework for Seamless Integrated Mobility (SIM). The research will focus on designing and implementing AI agents and leveraging service-oriented architectures to enhance accessibility, inclusivity, and efficiency in urban mobility systems.

Key responsibilities

• Conduct research on AI agents for multimodal transportation functions such as service bundling, demand-supply matching, and personalized service delivery.
• Develop user personas and analyze urban mobility challenges to inform platform design.
• Prototype AI models for real-time data processing and context-aware mobility services.
• Collaborate with the project team to integrate research findings into the SIM platform prototype.
• Present research results at academic conferences and publish in peer-reviewed journals.

Required qualifications

• Bachelor's or master's degree in computer science or engineering, transportation engineering, or a related field.
• Proficiency in programming languages such as Python and C++, preferably both.
• Background in AI, machine learning, or agent-based modeling.
• Interest in solving urban mobility challenges through innovative technologies.

Preferred qualifications

• Familiarity with service-oriented architectures or multimodal transportation systems.
• Experience with user-centered design or persona development.
• Expertise in data serialization languages such as YAML, JSON, and Protobuf, as well as data distribution and messaging protocols such as MQTT and Zenoh.
• Expertise in API protocols such as REST, GraphQL, WebSocket, and gRPC, along with query languages such as SQL, KQL, PromQL, and LogQL.

MSc Student in Seamless Integrated Mobility

We are seeking a motivated MSc student to join a research project focused on developing a unified AI-based platform for Seamless Integrated Mobility (SIM). This role offers hands-on experience in applying AI and service-oriented architectures to solve real-world challenges in urban mobility.

Key responsibilities

• Assist in the design and implementation of AI agents for specific mobility functions, focusing on multi-criteria end-to-end trip planning.
• Analyze urban mobility challenges and develop user personas to guide platform development.
• Work collaboratively with the project team to ensure research goals are met.
• Contribute to project documentation and publications.

Required qualifications

• Bachelor's degree in computer science or engineering, transportation engineering, or a related field.
• Basic understanding of AI, machine learning, and optimization algorithms.
• Interest in urban mobility and sustainable transportation systems.

Preferred qualifications

• Familiarity with service-oriented architectures, agent-based systems, or route optimization.
• Background in user-centered design or multimodal mobility systems.
• Expertise in data serialization languages such as YAML, JSON, and Protobuf, as well as data distribution and messaging protocols such as MQTT and Zenoh.
• Expertise in API protocols such as REST, GraphQL, WebSocket, and gRPC, along with query languages such as SQL, KQL, PromQL, and LogQL.