Postdoc position in Deep Learning for Automated Modular Computer-Aided Design

Applications are invited for a one-year post doc. position at the Department of Electrical and Computer Engineering at Aarhus University. This position is for the project “AI-supported Modular Design and Implementation” supported by Thomas B. Thriges Foundation and the Industriens Foundation with cooperating partners from DTU and industrial beneficiaries.

The postdoctoral researcher will join our research group, Machine Learning and Computational Intelligence (MaLeCI), which is a dynamic and diverse team of talented and highly-motivated researchers conducting cutting-edge research in Machine Learning, Deep Learning, Computer Vision, Financial Data Analysis and Geometric Deep Learning.

Our group is equipped with the high-performing computational resources (the best NVIDIA GPUs, embedded GPUs for light-weight deep learning, drones, etc) facilitating high-ending AI research.

Checkout https://ece.au.dk/en/research/key-areas-in-research-and-development/signal-processing-and-machine-learning/machine-learning-and-computational-intelligence/people for more information about the MaLeCI group, researchers and the current research projects.

Expected start date and duration of employment
The position is available from 1 October 2024, or as soon as possible thereafter. The position is for one year, with the possibility of extension of up to one more year.

Job description
The main objective of this multidisciplinary project is to develop deep learning methods, including convolutional neural networks, transformers, and graph convolutional networks, for (semi)-automated CAD design, grouping, segmenting, and synthesizing CAD models, to support product design decisions by analyzing the similarity of CAD designs and providing the next step design suggestions to CAD engineers. Through cutting-edge research and collaboration with industrial partners, the team will develop high-performing methodologies and demonstrate their performance on both benchmark and real-world data.

Throughout this project, we will collaborate with researchers with both mechanical engineering and computer science/engineering background as well as relevant industrial case companies for testing and prototyping our proposed deep learning design assistance tool on real data and show the effectiveness of our methods in facilitating design process and implementing modularity in manufacturing.

Your profile
Applicants should hold a PhD in computer engineering, computer science, informatics, or other related disciplines. Moreover:

• Solid understanding of Deep Learning algorithms and architectures.
• Excellent programming skills in Python deep learning frameworks such as TensorFlow, Keras, PyTorch, etc, and proficiency in writing scripts for data preprocessing, deploying deep learning models, model training, and evaluation.
• Experience with collaborative software development, such as Git and version control systems.
• Familiarity with Geometric Deep Learning is a plus.
• Strong publication record in high-profiled international journal and conference proceedings.
• Good verbal and written English communication skills.

Who we are
About the Department of Electrical and Computer Engineering:
Electrical and computer engineering are closely related engineering disciplines that focus on the development of hardware and software for intelligent units and networks. This includes hardware at system and component levels as well as many different types of software for controlling electronic devices and networks.

The research areas within the Electrical and Computer Engineering Department support the development within this area. The outcome greatly influences our daily lives as advanced technologies are incorporated into an increasing number of products, for example in industrial processes, at hospitals and in information infrastructures.

What we offer
The department/centre offers:

• A collaborative, supportive and friendly environment.
• A well-developed research infrastructure, powerful computational resources and state-of-the-art equipment.
• An interdisciplinary environment with many national, international, and industrial collaborators
• The opportunity to co-supervise PhD and MSc students working in related topics
• A workplace characterized by professionalism, equality and a healthy work-life balance.

Place of work and area of employment
The place of work is Finlandsgade 22, 8200 Aarhus N, Denmark, and the area of employment is Aarhus University with related departments. The project includes meetings with cooperating partners from DTU and industrial beneficiaries.

Contact information
Further information about the position may be obtained from Professor Alexandros Iosifidis, email: [email protected].

Deadline
Applications must be received no later than 15 August, 2024.

Application procedure
Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment committee if necessary, – the head of department selects the candidates to be evaluated. All applicants will be notified whether or not their applications have been sent to an expert assessment committee for evaluation. The selected applicants will be informed about the composition of the committee, and each applicant is given the opportunity to comment on the part of the assessment that concerns him/her self. Once the recruitment process is completed a final letter of rejection is sent to the deselected applicants. Letter of reference
If you want a referee to upload a letter of reference on your behalf, please state the referee’s contact information when you submit your application. We strongly recommend that you make an agreement with the person in question before you enter the referee’s contact information, and that you ensure that the referee has enough time to write the letter of reference before the application deadline.
Unfortunately, it is not possible to ensure that letters of reference received after the application deadline will be taken into consideration. Formalities and salary range
Technical Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Taxation and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities.

Salary depends on seniority as agreed between the Danish Ministry of Taxation and the Confederation of Professional Associations.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.

Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners. Read more here. Please find more information about entering and working in Denmark here.

Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here.

The application must be submitted via Aarhus University’s recruitment system, which can be accessed under the job advertisement on Aarhus University's website.
Aarhus University
Aarhus University is an academically diverse and research-intensive university with a strong commitment to high-quality research and education and the development of society nationally and globally. The university offers an inspiring research and teaching environment to its 38,000 students (FTEs) and 8,300 employees, and has an annual revenues of EUR 935 million. Learn more at www.international.au.dk/

Department: Sign. Processing & Mach. Learning/Sign. Processing & Mach. Learning

Deadline: 15 August 2024

Location: Aarhus N Finlandsgade 22