DOCTORAL RESEARCHER (SHARED HUMAN-ROBOT CONTROL) / VÄITÖSKIRJATUTKIJA (JAETTU IHMIS-ROBOTIN OHJAUS)

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The Advanced Learning, Control and AutomatioN (ALCAN) Research Group, part of the Automation Technology and Mechanical Engineering Unit at Tampere University, Finland, is pleased to announce the opening of a Doctoral Researcher position. This position focuses on “Shared Human-Robot Control.” It offers an exciting opportunity to engage in innovative research at the intersection of optimal control, machine learning and robotics.

JOB DESCRIPTION

As technology increasingly integrates human and machine/robot operations, ensuring robust, seamless control in environments with variable or limited connectivity becomes a critical challenge. The successful candidate for this Doctoral Researcher position will explore advanced methods for shared human-robot control that dynamically adapt to communication failures or delays. This research will focus on enabling human operators to interact with local edge controllers that maintain safety and performance, even under unpredictable network conditions. Central to this effort is developing systems that learn human operator objectives and preferences over time, ensuring a fluid transition between manual input and autonomous or safety controller interventions. By testing these approaches in both simulated and real-world scenarios, this work aims to deliver reliable, data-efficient, and explainable control solutions that optimize productivity and safety across diverse applications, ranging from remote robotics to heavy machinery in forestry, construction, mining, and logistics.
The direction of the research will be shaped by the project tasks. However, the research focus and responsibilities can be tailored to align with the candidate’s skills, experience, and interests. The position involves collaborating with a multidisciplinary team to advance current knowledge and technology in this field, publishing findings in reputable journals, presenting at international conferences, and may include a few months of mobility to a European partner for collaborative work during the research stages.

REQUIREMENTS

Applicants are expected to meet the following criteria:

• Educational Qualification: A master’s degree in Engineering with a background in mechatronics engineering, computer science, mechanical engineering, electrical engineering, or a related field at the time of application.
• Academic Background: A solid background in optimal control and machine learning is necessary. Additional knowledge in optimization, reinforcement learning, and model predictive control is highly desirable.
• Technical Proficiency: Strong skills in Python and MATLAB based programming are essential. Particular experience in common frameworks (e.g., JAX, PyTorch, and CasADi) would be a big plus. Proficiency in C++ would also benefit hardware implementations. Candidates should also be willing to further develop their coding efficiency.
• Language Skills: Proficiency in both written and spoken English is required. Applicants should possess excellent communication and interpersonal skills. Proficiency in Finnish is not required.
• Working Style: Ability to work both independently and as part of a team. Candidates should demonstrate a balance of autonomy and collaborative skills.
• Additional Competencies: A strong willingness to engage deeply in the research field of robotics and autonomous systems is highly appreciated. An interest in pursuing a research career and the capacity for hard work are also valued.

Please note that the eligibility of the student for admission criteria in doctoral program will be verified before final decision is made. Please visit the admissions webpage for more information on eligibility requirements.
Tampere University is a unique, multidisciplinary, forward-thinking, and evolving community. Our values are openness, critical thinking, diversity, learner-centredness, courage, erudition, and responsibility. We hope you can embrace these values and promote them in your role.

Please refer the Job description for details