The goal is to resolve how financial settings can adapt practices or propose solutions for designing green credit scoring models. This will facilitate improved access to investment and credit, thereby promoting fair and sustainable economic growth. You will be a member of the MSCA Industrial Doctoral Network on Digital Finance, a European Research and Training programme with several leading European universities and companies involved, such as the European Central Bank and the Bank for International Settlements. You will attend several European PhD courses and participate in extended research stays abroad.
You will join the Industrial Engineering and Business Information Systems (IEBIS) section of the High-tech Business & Entrepreneurship Department (HBE) at the Faculty of Behavioral Management and Social Sciences (BMS).
Background
This Ph.D. position is one four positions at the University of Twente (UT) and one of 19 positions in the context of the international Marie Sk?odowska- Curie Actions project DIGITAL. For the general description of DIGITAL, please check this page. Information about all other positions is available at EURAXESS, if you would be interested in any of the other positions as well, clearly state that in your cover letter.
DIGITAL' main goal? To significantly advance the methodologies and business models for Digital Finance through five interconnected research objectives:
1. Ensure sufficient data quality to supply to the EU's efforts of building a single digital market for data 2. Address deployment issues of complex artificial intelligence models for real-world financial problems 3. Validate the utility of innovative explainable artificial intelligence (XAI) algorithms to financial applications and extend existing frameworks 4. Design risk management tools concerning the applications of Blockchain technology in Finance 5. Simulate financial markets and evaluate products with a sustainability component
The description here focuses on the specific position "Modelling green credit scores for a network of retail and business clients" (mainly included in objective #5), outlining the project's key takeaways and desired skills of future members of the network.
The challenge
In an ever-evolving financial landscape where the process industry responds to the growing demand for sustainable business models, the significance of AI in shaping decision-making cannot be overstated. Using the power of Machine Learning (ML) models, our project will examine financial investments and credit risk indicators. While these AI techniques have found widespread application in traditional financial domains, a noticeable gap exists in addressing the unique dynamics of businesses. Existing financial models often overlook the environmental and social intricacies of credit risk models, elements that can significantly impact access to credit and thereby hamper economic growth.
This Ph.D. project is committed to a comprehensive exploration of the intersection between finance and sustainable business models, with a specific focus on credit risk assessment through the use of AI. Our goal is to provide innovative AI tools and models to businesses and society to promote sustainable financial strategies based on principles of sustainability, fairness, and transparent credit risk assessment. Are you prepared to reshape the financial sector by improving risk assessments and investment choices, all while advocating for sustainability and environmental stewardship? If this resonates with you, this position could be your ideal opportunity!
Your profileYou are a highly motivated, enthusiastic researcher who is driven by curiosity;
You have a master's degree or equivalent experience in Business, Economics, Engineering, Information Technology, Mathematics, Computational Science or related fields;
You have a strong passion and outstanding skills in data science and experience working with Python;
You have knowledge of quantitative modeling of financial markets, econometric techniques, machine learning, or quantitative empirical research methods;
You have the ability to work on real-world problems in an interdisciplinary and internationally oriented environment;
You have good communication skills and an excellent command of English.
You have good programming skills. Experience with machine learning libraries (e.g., TensorFlow, PyTorch) is required.
You have knowledge and experience with ML design and implementation, working with multiple libraries/platforms (e.g., Pandas, Sklearn, Conda, Github, etc.).
You have strong mathematical background, in particular statistics & probability, linear algebra, calculus, optimization, and Markov decision processes.
You have knowledge of financial engineering concepts such as credit risk assessment and mitigation, probability of default, credit portfolio management.
You have interest in practical applications of ML and AI, with attention to aspects such as explainability, ethics, and honest usage of customers' data.
You have familiarity with credit risk modeling processes and regulations is a plus.
The researcher working on this project will be a member of the coordinator team and the doctoral training team, thus contribution to coordination (research, technical, or financial) and other activities of the MSCA Doctoral Network is a substantial element of the candidate's work and professional development plan. We further emphasize that all Ph.D. candidates in DIGITAL will collaborate, therefore involvement and contribution to the topics and activities of DIGITAL is an important element of this position.
Interested and motivated candidates are encouraged to apply, even when they do not yet possess all desired skills. Through dedicated learning and doctoral training, you will be able to develop relevant skills on the job.
Are you interested to be part of our team?
Please upload your application before May 31, 2024.
Your application should include
Additional information can be acquired via email from dr. Marcos R. Machado, dr. Xiaohong Huang, or dr. Joerg R. Osterrieder via email: msca- [email protected].
About the departmentThe HBE cluster is dedicated to encouraging a supportive and inclusive working culture. Our aim is that all job applicants are given equal opportunities. When we select candidates for employment, it will be on the basis of their competence and ability. To support workforce diversity, we are open to offering flexible working conditions on an individual basis to support work- life balance, which may include contract of employment, working hours and location, or childcare arrangements.
The High Business Entrepreneurship corporate video can be watched via this link.
About the organisationThe Faculty of Behavioral, Management and Social sciences (BMS) aims to play a key role in understanding, jointly developing and evaluating innovations in society. Technological developments are the engine of innovation. As a technical university that puts people first, we tailor them to human needs and behavior and use social engineering to integrate them into society. We also ensure adequate governance at public and private level, and robust, inclusive and fair organizational structures. We do this by developing, sharing and applying high-quality knowledge in Psychology, Business Administration, Public Administration, Communication Sciences, Philosophy, Educational Sciences and Health Sciences. Our research and education in these disciplines revolves around tackling and solving societal challenges. The research programs of BMS are closely linked to the research of the UT institutes Mesa+ Institute for Nanotechnology, TechMed Center and Digital Society Institute.
As an employer, the Faculty of BMS offers work that matters. We equip you to create new possibilities for yourself and for our society. With us, you will become part of a leading technical university with increasing, positive social impact. We offer an open, inclusive and entrepreneurial atmosphere, in which we encourage you to make healthy choices, for example through our flexible, adaptable benefits.
Want to know more? Machado, M.R. (Marcos)Assistant Professor
Machado, M.R. (Marcos)Assistant Professor
Do you have questions about this vacancy? Then you can contact Marcos for all substantive questions about this position and the application procedure. For general questions about working for the UT, please refer to the chatbot.
ContactPhone:+31534899045
Email:[email protected]
How to apply Step 1Apply. When you see a vacancy that appeals to you, you can apply online. We ask you to upload a CV and motivation letter and/or list of publications. You will receive a confirmation of receipt by e-mail.
Step 2Selection. The selection committee will review your application and you will receive a response within 2 weeks after the vacancy has been closed.
Step 31st interview. The 1st (online or in person) meeting serves as an introduction where we introduce ourselves to you and you to us. You may be asked to give a short presentation. This will be further explained in the invitation.
Step 42nd interview. In the second interview, we will further discuss the job content, your skills and your talents.
Step 5The offer. If the conversations are positive, you will be made a suitable offer. If applicable, we will sign you up for screening.
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