PhD student in Digital Sensing and Modelling of Travel Behaviour and Mental Health

 

DTU Management’s Transport Division would like to invite applications for a 3-year PhD position starting no later than September 1st, 2021. The successful candidate will join the Machine Learning for Smart Mobility Group and will work under the supervision of Associate Professor Carlos Azevedo and Senior Researcher Sonja Haustein in collaboration with the Faculty of Medicine of the University of Lisbon.

This PhD project is part of a larger project entitled “eMOTIONAL Cities - Mapping the cities through the senses of those who make them”, funded by the EU Commission’s H2020 Framework and part of the European Cluster on Urban Health.

Project Background
The eMOTIONAL Cities project was designed to provide robust scientific evidence on how the natural and built urban environment affects human cognitive and emotional processing. Furthermore, it aims to map such neurobiological reactivity through time and space as the urban landscape change. Grasping the spatial cognition of the citizens’ behaviour and decisions while interacting with their real-life surroundings will be a breakthrough, as it will foster more inclusive urban design resulting in better individual health and well-being. 

This specific PhD project will focus on the joint sensing and modelling of travel decision, neuro- and bio-signals and mental health, in outdoor environments, with different groups of people and across various urban scenarios.

Together with our team (with a background in discrete choice modelling, psychology, machine learning and technology management) the candidate will design, pilot and implement the data collection architecture for outdoor natural experiments, combining existing smartphone- and biosensing-based technologies targeting the exploration of causal relationships between multiple urban environments and individual behavioural signals. Participants will be asked to carry smartphones with apps specifically designed for customized adaptive stated perception surveys regarding context-specific built and travel environment, as well as for detailed data on daily travel and activity patterns across multiple days. Moreover, participants will also wear several types of environmental (for measuring climate and outdoor comfort data) and neurobiological (e.g.: eye tracking glasses, wearable EEG, physiological biosignals) sensors.

Behaviour modelling methods from discrete choice, cognitive processes and machine learning will be used to construct the linkage between context and environmental stimulus, neurophysiological metrics, stated and measured emotional and cognitive indicators and the underlying travel and activity participation decision making.

Finally, the modelled relationships will be integrated in a new activity-based travel behaviour model for scenario evaluation at the urban scale.

Overall, this research lies in the intersection between Behavioural Modelling and Digital Sensing. This is a unique opportunity to build your research profile under a collaborative large network sustained by a European-funded project.

We are looking for excellent applicants with MSc background on Behavioural Modelling, Cognitive Neuroscience, Mental Health, Transportation, Computer Science, Applied Statistics or related.

Responsibilities and tasks

• Design, implement and pilot the data collection architecture for outdoor natural experiments
• Develop mathematical models of individual behaviour through the mapping of the underlying neuro- and cognitive- processes and its relationship with mental health
• Collaborate with researchers from behavioural modelling, computational and neurosciences in a truly interdisciplinary environment.
• Co-author scientific papers aimed at high-impact journals.
• Participate in international conferences.
• Participate advanced classes to improve academic skills
• Carry out work in the area of dissemination and teaching as part of the overall PhD education.

Qualifications 

• A MSc degree in Behavioural Modelling, Cognitive Neuroscience, Mental Health, Transportation, Computer Science, Applied Statistics or related.
• Excellent background in statistics and probability theory is required.
• Good programming capabilities in at least one scientific language is required.
• Experience with digital sensing is favoured.
• Behavioural modelling or mental health disciplines in the education background is favoured.

The following soft skills are also important:

• Curiosity and interest about current and future mobility challenges and digital technologies.
• Good communication skills in English, both written and orally.
• Experience in writing and publishing scientific papers is an advantage.
• Willingness to engage in group-work with a multi-national team.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide. 

Assessment
The assessment of the applicants will be made until the position is filled and no later than July 1st 2021. 

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and terms of employment
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. 

You can read more about career paths at DTU here. 

Further information
For more information, please contact Carlos Lima Azevedo climaz@dtu.dk or Sonja Haustein sonh@dtu.dk.  

You can read more about the Machine Learning for Smart Mobility group at http://mlsm.man.dtu.dk/ and DTU Management at www.man.dtu.dk/english. 

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. 

Application procedure
Your complete online application must be submitted no later than 20 June 2021 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma
• Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

MLSM
The Machine Learning for Smart Mobility group belongs to the Transport division of the Department of Technology, Management and Economics (DTU Management) at DTU. The division conducts research and teaching in the field of traffic and transport behaviour and planning, with particular focus on behaviour modelling, machine learning and simulation.

Who are we
DTU Management conducts excellent research in the intersection between management, technology, and economics. We develop solutions in close cooperation with companies and public authorities. Our research aims at strengthening welfare, productivity, and sustainability within the society. A key element is the role of technology and its interaction with industry and individuals. The department’s research is divided in four divisions: Innovation, Management Science, Sustainability and Transport. Furthermore, the department hosts a UN Collaborating Centre. The UN DTU Partnership conducts research, policy analysis and advising on a global scale. The department offers a wide range of courses and programs at BSc, MSc, and PhD level across DTU’s study programs. DTU Management employs about 320 people. We offer an international environment with around 50 different nationalities represented at the department.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,900 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.

Apply for this job

Apply no later than 20 June 2021
Apply for the job at DTU Management by completing the following form.

Apply online

PhD scholarship in Solid Oxide Electrolysis Cells

 

Do you want to contribute to a sustainable future based on solid oxide electrolysis cell technology? At the Department of Energy Conversion and Storage (DTU Energy) at the Technical University of Denmark our research is targeting exactly this, and we are looking for a new PhD student.

Displacement of fossil fuels by renewable energy (RE) is a global issue with inherent challenges of balancing electricity supply and demand. Solid oxide electrolysis cells (SOECs) can convert electricity from RE sources into hydrogen, CO or methane and hence contribute to an excess electricity offtake. The produced gas can be converted into liquid hydrocarbon fuels for the transportation sector, sold to other high value markets, or converted back to electricity at peak demand and hereby reduce the carbon footprint.

At DTU Energy we have been carrying out R&D in sustainable energy conversion technologies and especially solid oxide electrolysis cells for many years and we are among the world’s leaders in research and development in this area. We have excellent facilities and competences for fabrication, modeling, testing and characterization of devices.

In this specific project, which is part of the Next Generation Power2X for Renewable Energy Conversion and Storage funded by the Innovation Fund Denmark, we aim to develop a highly efficient and cost competitive SOEC-based Power2X (P2X) technology to facilitate integration of fluctuating RE into the future energy system and thus provide sustainable solutions for future urban transport and chemical industry. We aim in NEXP2X to develop low cost and high performing SOEC, by lowering the operating temperature with >100C thus allowing for usage of cheap components, leading to a cost reduction by 50%. As a PhD-student you will help us with this by researching how to optimize SOEC cells with regard to microstructure and composition, exploring different electro-catalysts, developing protective coatings for cheap stainless steels, and finally performance and durability testing of your developed SOEC cells. You will be working in a team with experts in electrolysis technologies and energy storage, with industry, and other university departments.

Qualifications
Qualified applicants must have:

• a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.
• a master's degree in chemistry, chemical engineering, materials science, physics or similar
• Be excellent in establishing an overview and take responsibility
• Ability to work independently, to plan and carry out complicated tasks.
• Good communication skills in English, both written and spoken.
• Knowledge/experience on the subjects of electrochemical characterization of solid oxide cells, electrode infiltration, and interconnect corrosion is further advantageous.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.

Assessment
The assessment of the applicants will be made by Professor MSO Ming Chen and Head of Section, Professor Rasmus Bjørk.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about career paths at DTU here.

Further information
Further information about the project may be obtained from Professor Ming Chen tel.: +45 46 77 57 57.

You can read more about DTU Energy on www.energy.dtu.dk/english

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.

Application
Please submit your online application no later than 30 June 2021 (Danish time). 

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma
• Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Energy
The Department of Energy Conversion and Storage is focusing on functional materials and their application in sustainable energy technology. Our research areas include fuel cells, electrolysis, solar cells, electromechanical converters, sustainable synthetic fuels, and batteries. The Department, which has more than 200 employees, was founded in 2012. Additional information about the department can be found on www.energy.dtu.dk

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,900 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland. 

Apply for this job

Apply no later than 30 June 2021
Apply for the job at DTU Energy by completing the following form.

Apply online

PhD scholarship in Integrated Photonic Circuits for All-Optical Reservoir Computing

 

The Machine Learning in Photonic Systems group at DTU Fotonik seeks a candidate for a PhD project on integrated photonic circuits for all-optical reservoir computing. The 3-year PhD position is funded by the Villum Foundation through the Villum Young Investigator Programme: ‘OPTIC-AI – Optical processing unit for high-speed AI applications’.

Responsibilities and qualifications
The current digital implementations of machine learning algorithms are limited in speed and energy consumption by the electronics hardware platform they are implemented on. Moving towards all-optical implementations can overcome these challenges. Therefore the key objective of the OPTIC-AI project is to develop a new optical processing unit for implementing reservoir computing, and machine learning in general, on a photonic hardware platform.

Your Ph.D. project will be hosted within the OPTIC-AI team, part of the Machine Learning in Photonic Systems group at DTU Fotonik. 

Within the OPTIC-AI team (3 PhD students, 1 Postdoc and PI), you will work bridging between the numerical analysis of optimized integrated photonic circuits and the design of the circuits’ layout for fabrication in commercial foundries. The project will start by focusing on current demonstrations of optoelectronics reservoir computing and extreme machine learning to subsequently move into fully optical implementations to be realized with photonic integrated circuits (PICs). 

Your overall responsibility will be to use both numerical methods and process design kits (PDKs) to address some of (but not limited to) the research topics listed below:

• Photonic neural networks
• Optoelectronics implementation of reservoir computing
• Silicon photonic circuits
• Design of linear and nonlinear integrated waveguides
• Optimization of photonic circuits to achieve specific functionalities

In general, you are expected to:

• Help to develop numerical simulation code in Matlab/Python
• Propose complex networks of photonic components to implement photonic reservoirs and neural networks.
• Optimize PICs based on a combination of custom-developed code and commercial software (e.g. Lumerical)
• Design PICs by using foundry-provided PDKs

Candidates are expected to have experience in optics, especially integrated optics. Additionally, the candidates are required to have good communication skills in English (both written and spoken) and a proven ability to work independently, plan, and carry out complicated tasks. 

The candidates are expected to describe their previous experience with numerical simulations and/or PIC design in the cover letter

Moreover, the following skills will receive additional consideration:

• Theoretical understanding of extreme learning machine and/or reservoir computing
• Theoretical understanding of nonlinear optics
• Experience with numerical implementations of machine learning algorithms
• Experience with machine learning frameworks such as Tensorflow and Pythorc
• Innovative skills and the ability to generate new ideas

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide. 

Assessment
The assessment of the applicants will be made by Senior Researcher Francesco Da Ros. 

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. The starting date is expected approx. September 2021.

You can read more about career paths at DTU here. 

Further information
Further information may be obtained from Senior Researcher Francesco Da Ros (fdro@fotonik.dtu.dk).

You can read more about DTU Fotonik on www.fotonik.dtu.dk. 

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. 

Application procedure
Your complete online application must be submitted no later than 30 June (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma
• Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply. 

DTU Fotonik has 210 employees with competencies in optics and is one of the largest centers in the world based solely on research in photonics. Research is performed within optical sensors, lasers, LEDs, photovoltaics, ultra-high-speed optical transmission systems, bio-photonics, nano-optics, and quantum photonics. 

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,900 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.

Apply for this job

Apply no later than 30 June 2021
Apply for the job at DTU Fotonik by completing the following form.

Apply online