PhD Position in Physics-Informed Machine Learning for Optimization of Chemical Processes

We are seeking a highly motivated PhD student to comine Machine Learning (ML) with Chemical Engineering.

We are seeking a highly motivated PhD student to work on the combination of chemical engineering and Machine Learning (ML) for the modeling and optimization of chemical processes.

In this PhD project, you will develop novel tools for the multi-scale modeling and optimization of large scale chemical and energy processes. To integrate the scales, the research project will explore the potential of state-of-the-art ML models (i.e., Physics-Informed Neural Networks, PINNs). The PINNs or hybrid models will be used to learn the solution of differential equations that describe underlying mechanistic processes at different scales (ranging from the catalyst scale to the plant scale). The project is part of a direct collaboration with a leading energy company that provides experimental, operational, and design data. The project team also includes a postdoc who will co-supervise the PhD project.  

In the project, you will conduct research in the process systems engineering (PSE) domain. Your work will be implemented code in state-of-the-art programming languages (e.g., Python or Julia) and you will use cutting-edge ML frameworks (e.g., PyTorch). Moreover, you will apply and develop advanced optimization techniques for process design (e.g., superstructure optimization). Working in a team, you will use version control (e.g., Git) and unit tests for joint software development.

Ultimately, your project can have a high impact on sustainable process solutions. You will be working together with a leading industry partner who will apply your tool for the design of large-scale process solutions. Thus, your research results have a direct impact on energy consumption, emissions, and costs at a large scale.

We support you to become a future leader in AI in chemical engineering. This project will prepare you for a future career in academia and industry. We provide an excellent working environment for your research. Most importantly, we have a great team. We are working in teams and we support each other! Moreover, we have access to cutting-edge computing facilities.

Besides your research, you will get the chance to supervise graduate students during your PhDs. Moreover, you will be involved in teaching activities as a Teaching Assistant (e.g., a course on AI in chemical engineering).

Last but not least, we foster diversity, inclusion, and equality actively in our group. We create and maintain a common speak up culture in our group. Also, we create a family friendly workplace where we find individual concepts that balance family and work for our everyone.

We are very much looking forward to your application.

We are looking for candidates that meet the following criteria:

• Hold a MSc in STEM (preferably in Chemical Engineering or computer science)
• Prior expertise in process sytems engineering and/or machine learning
• Excellent programming skills in Python or Julia are essential. Knowledge of other programming languages is desired.
• Experience with relevant Python libraries (TensorFlow/PyTorch, the python scientific stack) is necessary
• Familiarity with version control, for example, git
• Prior knowledge of chemical process modeling
• Ability to work in a team and mentor other students
• Ability to communicate scientific results
• Excellent oral and written English with good presentation skills.

Preferred Qualifications

• Experience with continuous integration and testing pipelines.
• Experience with superstructure optimization and mixed-integer nonlinear optimiation (MINLP)

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

With more than 1,000 employees, including 135 pioneering principal investigators, as well as a population of about 3,400 passionate students, the Faculty of Applied Sciences is an inspiring scientific ecosystem. Focusing on key enabling technologies, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we train students in broad Bachelor's and specialist Master's programmes with a strong research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science & Technology, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers and science communicators.

Click here to go to the website of the Faculty of Applied Sciences.

For more information about this vacancy, please contact Dr. Artur Schweidtmann.

Are you interested in this joining our team? Please apply before 15-02-2023 via the application button and upload:

• A motivation letter (max 1 page);
• Your curriculum vitae;
• Your BSc and MSc academic records (including courses and grades);
• The names and contact details of two references.  

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post. Acquisition in response to this vacancy is not appreciated.

The available position will be filled as soon as possible (i.e. once a suitable candidate is found). This means that the selection of candidates will already start before the application deadline

We are seeking a highly motivated PhD student to comine Machine Learning (ML) with Chemical Engineering.

We are seeking a highly motivated PhD student to work on the combination of chemical engineering and Machine Learning (ML) for the modeling and optimization of chemical processes.

In this PhD project, you will develop novel tools for the multi-scale modeling and optimization of large scale chemical and energy processes. To integrate the scales, the research project will explore the potential of state-of-the-art ML models (i.e., Physics-Informed Neural Networks, PINNs). The PINNs or hybrid models will be used to learn the solution of differential equations that describe underlying mechanistic processes at different scales (ranging from the catalyst scale to the plant scale). The project is part of a direct collaboration with a leading energy company that provides experimental, operational, and design data. The project team also includes a postdoc who will co-supervise the PhD project.  

In the project, you will conduct research in the process systems engineering (PSE) domain. Your work will be implemented code in state-of-the-art programming languages (e.g., Python or Julia) and you will use cutting-edge ML frameworks (e.g., PyTorch). Moreover, you will apply and develop advanced optimization techniques for process design (e.g., superstructure optimization). Working in a team, you will use version control (e.g., Git) and unit tests for joint software development.

Ultimately, your project can have a high impact on sustainable process solutions. You will be working together with a leading industry partner who will apply your tool for the design of large-scale process solutions. Thus, your research results have a direct impact on energy consumption, emissions, and costs at a large scale.

We support you to become a future leader in AI in chemical engineering. This project will prepare you for a future career in academia and industry. We provide an excellent working environment for your research. Most importantly, we have a great team. We are working in teams and we support each other! Moreover, we have access to cutting-edge computing facilities.

Besides your research, you will get the chance to supervise graduate students during your PhDs. Moreover, you will be involved in teaching activities as a Teaching Assistant (e.g., a course on AI in chemical engineering).

Last but not least, we foster diversity, inclusion, and equality actively in our group. We create and maintain a common speak up culture in our group. Also, we create a family friendly workplace where we find individual concepts that balance family and work for our everyone.

We are very much looking forward to your application.

We are looking for candidates that meet the following criteria:

• Hold a MSc in STEM (preferably in Chemical Engineering or computer science)
• Prior expertise in process sytems engineering and/or machine learning
• Excellent programming skills in Python or Julia are essential. Knowledge of other programming languages is desired.
• Experience with relevant Python libraries (TensorFlow/PyTorch, the python scientific stack) is necessary
• Familiarity with version control, for example, git
• Prior knowledge of chemical process modeling
• Ability to work in a team and mentor other students
• Ability to communicate scientific results
• Excellent oral and written English with good presentation skills.

Preferred Qualifications

• Experience with continuous integration and testing pipelines.
• Experience with superstructure optimization and mixed-integer nonlinear optimiation (MINLP)

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

With more than 1,000 employees, including 135 pioneering principal investigators, as well as a population of about 3,400 passionate students, the Faculty of Applied Sciences is an inspiring scientific ecosystem. Focusing on key enabling technologies, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we train students in broad Bachelor's and specialist Master's programmes with a strong research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science & Technology, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers and science communicators.

Click here to go to the website of the Faculty of Applied Sciences.

For more information about this vacancy, please contact Dr. Artur Schweidtmann.

Are you interested in this joining our team? Please apply before 15-02-2023 via the application button and upload:

• A motivation letter (max 1 page);
• Your curriculum vitae;
• Your BSc and MSc academic records (including courses and grades);
• The names and contact details of two references.  

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post. Acquisition in response to this vacancy is not appreciated.

The available position will be filled as soon as possible (i.e. once a suitable candidate is found). This means that the selection of candidates will already start before the application deadline