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PHD STIPEND IN STATISTICAL AND ML MODELLING WITH THE IMPLEMENTATION OF RISK STRATIFICATION FOR CANCER THERAPY

at Aalborg University
Published May 4, 2023
Location Aalborg, Denmark
Category Machine Learning  
Job Type Scholarship  

Description

Job description

This PhD stipend is funded by Sundhedsdonationer under the project“AI-based clinical decision-support tool for fast risk stratification of febrile neutropenia”. The project starts on 1st August 2023 and will be conducted in collaboration with researchers from Aalborg University Hospital(AAUH), Rigshospitalet(RH), and Aalborg University(AAU). The PhD call is for 3 years with a collaboration between AAU, AAU Copenhagen, and RH/Copenhagen University(office in Copenhagen) and the option to work from Aalborg as well if the best candidate prefers that.

The PhD student will work with an interdisciplinary team consisting of physician researchers in hematology and oncology, AI/ML experts, a pre-hospital research unit, and a microbiology team to support the project. The clinical team of the consortium has expertise in hematological, oncological, and microbiological specialties. The technical team of the consortium is specialized in statistics, AI/ML, mathematical modeling, algorithms development, and decision support tool(DST) implementation. The consortium has strong, international, and innovative research collaborations which comprise the full life cycle of developing and implementing statistical DST from basic science to strategic and applicable research. You can find more at:

https://www.rigshospitalet.dk/cll-lab

https://blodet.dk/

https://www.mp.aau.dk/research/research-areas/operations-research

 

Job Description

A frequent side effect of treating cancer is febrile neutropenia. Patients are frequently brought into the hematology and oncology departments as a result of treatment-related problems, mostly infections. The project's objective is to create and put into practice a reliable artificial intelligence/machine learning(AI/ML)-based methodology for dynamic models that predict febrile neutropenia(FN) risk for specific patients starting cancer treatment(reassessed at each cycle of treatment) and dynamic/ongoing risk assessment upon admission with FN. This project will have a significant effect on the accurate classification of patients as high and low-risk. By improving diagnostics of febrile neutropenia, the study aims to reduce mortality and length of stay in a hospital of patients.

The AI/ML-based method will be created using patient data gathered from DALYCA, LABKA, Miba, and other electronic health records(EHRs) from hematology departments. Blood test data, vital signs, and details about the cancer condition and its therapy, such as the diagnosis, the course of treatment, the required minimum neutrophil count for admittance, and previous FN outcomes, are all clinical factors of interest.

The focus of the PhD project is interdisciplinary research at the intersection of Statistics, Machine Learning, and Medical Data. Statistical analysis and interpretation of medical data, exploring different learning methods, comparing different machine learning models in clinical research, model sensitivity analysis, and clinical validation of the model are example research goals of this PhD stipend.

About the PhD study:

  • Develop data-driven risk stratification of febrile neutropenia
  • Analysis and management/cleaning of medical data
  • Statistical analysis for data validation and verification
  • Develop statistical methods for sensitivity analysis of AI-based models
  • Providing statistical input to trial designs
  • Lead the preparation of scientific publications towards ISI journals and highly-ranked international conferences

The PhD candidate is expected to have:

  • Bachelor’s and Master's degree or a similar in Statistics, Computer Science, Computer Engineering, Mathematics, Applied Mathematics, or equivalent.
  • Hands-on experience with Python, R, or other programming languages.
  • Quantitative skills and interest in applications of statistics in medical research.
  • Experience in creating and validating analysis datasets.
  • Strong analytical and experimental skills.
  • High level of written and spoken English.
  • Experience with signal processing as a plus.
  • Having worked with medical data before as an advantage.
  • Knowledge of machine learning and deep learning as an advantage.
  • Strong communicative and collaborative skills in an interdisciplinary environment

 

You may obtain further information from Associate Professor Lasse Hjort Kyneb Jakobsen, Department of Hematology, Aalborg University Hospital, email:lasse.j@rn.dk; Assoc. Prof. Peter Nielsen, Department of Materials and Production, Aalborg University, email:peter@mp.aau.dk, Dr. Rudi Agius, Department of Clinical Medicine, University of Copenhagen, email:rudi.agius@regionh.dk, concerning the scientific aspects of the stipend.

PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student at the Doctoral School of Engineering and Science in accordance with the regulations of Ministerial Order No. 1039 of August 27, 2013 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD student shall be assessed at regular points in time.

Shortlisting will be applied. This means that subsequent to the deadline for applications the head of department supported by the chair of the assessment committee will select candidates for assessment. All applicants will be informed whether they will be assessed or not.

For further information about stipends and salary as well as practical issues concerning the application procedure contact Ms. Katrine Eline Søndergaard, The Doctoral School at The Faculty of Engineering and Science, email: kes@adm.aau.dk.

For more information of The Doctoral School of Engineering and Science:www.phd.engineering.aau.dk

The application is only to be submitted online by using the"Apply online" button below.

AAU wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of personal background or belief.

 

Wages and employment

Appointment and salary as a PhD fellow are according to the Ministry of Finance Circular of 15 December 2021 on the Collective Agreement for Academics in Denmark, Appendix 5, regarding PhD fellows, and with the current Circular of 11 December 2019 on the employment structure at Danish universities.

Ref number

915-23025

 

Deadline

03.06.2023