Assistant Professor in Artificial Intelligence (201724)

At the Faculty of Engineering and Science, Department of Materials and Production, Section of Sustainable Production at the Copenhagen Campus, Aalborg University a position as an Assistant Professor in Artificial Intelligence is open for appointment from the December 1st, 2017 or soon hereafter and for 3 years. Department of Materials and Production (MP) is a wide-ranging research and educational environment at Aalborg University. The Department's mission is to meet the future's demands for new materials and production systems by directing the whole value chain from basic material understanding, materials' applications in mechanical constructions, industrial production and management. The department has several strong, international and innovative research groups which comprise everything from basic science to strategic and applicable research. The activities encompass research as well as education within materials, mechanics, physics, production technique, and industrial management and innovation. Benefitting the industry and additional collaborators several innovative and unconventional collaborations have been and are developed through interdisciplinary co-operations. Thereby, as an employee at the Department you will become a part of an international research environment, where focus is on innovation, knowledge sharing/building and interdisciplinary collaborations.

Job description

Research and teaching will be within the fields of Artificial Intelligence (AI), Machine Learning, Wireless Sensor Networks (WSN) and their applications in designing and optimizing autonomous systems. Applicants are ideally expected to have both: 

  1. AI research experience in one or more of the following: reinforcement learning, deep learning, Bayesian methods, statistical forecasting, intelligent robot control and/or perception, interactive learning systems;
  2. AI application experience in one or more of the following WSN areas: machine health monitoring, distributed sensors in green and agile manufacturing, and sensor/RFID applications of the internet-of-things.

Applicants must have a completed Ph.D. degree in either Computer Science, Electrical Engineering, Manufacturing Engineering or similar. Applicants should also have a technical profile and documented previous experience of applying their research within an industrial application domain (track record of industrial collaborations within their expertise fields). Industrial domains such as intelligent supply chains, intelligent transportation logistics, demand forecasting, telemetry, manufacturing, production will be looked upon positively. Applicants with experience in designing and developing autonomous systems (autonomous vehicles, autonomous warehouse, drones, smart grids, transport systems) will be prioritized.

 

Applicants must have teaching experience at postgraduate level. The teaching activities at AAU include teaching courses and supervising student projects in the M.Sc.Eng. programme in Autonomous Systems, the M.Sc.Eng. programme in Operations and Management Engineering, the B.Sc.Eng. programme in Manufacturing and Operations Engineering, as well as some other programmes. Teaching topics may cover Machine Learning, Big Data, Smart Sensors, and related fields. Furthermore, teaching also includes supervising students in semester projects with industry collaborations.

Research will be conducted jointly with colleagues in both RVMI group (Robotics, Vision and Machine Intelligence) and LSCR group (Logistics and Supply Chain Research), in close collaboration with external industry and research partners locally, nationally and internationally. The successful candidates are expected to contribute actively to ongoing research (e.g. sensor data analysis and machine learning applications within industrial production and/or transportation logistics) and the development of new research projects.

You may obtain further professional information from Associate Professor Gang Chen, Phone +45 9940 3034  or email gc@m-tech.aau.dk                         
 
Qualification requirements:

Appointment as an Assistant Professor presupposes scientific qualifications at PhD–level or similar scientific qualifications. The research potential of each applicant will be emphasized in the overall assessment. 

Appointment as an Assistant Professor cannot exceed a period of four years in total in a temporary position (appointment at Assistant Professor level cannot exceed a period of eight years in total in Denmark). 

The application must contain the following: 

  • A statement outlining your reasons for applying, and intentions and visions with, the position.
  • Your curriculum vitae, including personal data, educational background, scientific qualifications, dissemination skills, participation in committees and boards, and additional qualifications relevant for the position.
  • Copies of relevant diplomas (Master of Science and PhD). On request you could be asked for an official English translation.
  • A complete list of publications.
  • Publications you wish to be considered by the assessment committee. You may attach up to 5 publications.
  • A specification of your teaching qualifications relative to the teaching portfolio. If this is not enclosed you must include an explanation for its absence.
  • References/recommendations.

An assessment committee will assess all candidates. 

The applications are only to be submitted online by using the "Apply online" button below.

For further information concerning the application procedure please contact Lisbeth Palmelund by mail lmp@adm.aau.dk  or phone (+45) 9940 7553.

Information regarding guidelines, ministerial circular in force, teaching portfolio and procedures can be seen here. 

Agreement

Employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities (the Appointment Order) and the Ministry of Finance's current Job Structure for Academic Staff at Universities. Employment and salary are in accordance with the collective agreement for state-employed academics.

Vacancy number

201724

Deadline

Sat Sep 30 00:00:00 CEST 2017

Apply online

Online ansøgning - gode råd

Online ansøgning - gode råd

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