PhD candidate 'Artificial Intelligence (A.I.) in neuro-oncology: from tumor-characteristics to patient outcome'

27 Feb 2024
Job Information

Organisation/Company

Radboud University Medical Center (Radboudumc)

Research Field

Medical sciences

Researcher Profile

Recognised Researcher (R2)
First Stage Researcher (R1)

Country

Netherlands

Application Deadline

18 Mar 2024 - 23:00 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Hours Per Week

36.0

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

We are looking for a PhD candidate who wants to join our team and is keen to optimize research in the use of Artificial Intelligence (A.I.) in neuro-oncology imaging and generate relevant insights into the relation between A.I.-generated characteristics and outcome in neuro-oncology patients and impact of these findings on clinical decision making. Are you our new PhD candidate?

This position is fully funded by the Interreg VI grant for the project IMAGINATION. This project is in collaboration with Radboudumc, Universitätsklinikum Düsseldorf and Universitatsklinikum Münster.

Neuro-oncological disease is subdivided into two subtypes: primary neuro-oncological diseases (e.g. glioblastoma) and secondary neuro-oncological diseases (i.e., brain metastases). Imaging by use of Magnetic Resonance Imaging (MRI) plays an important role in diagnosis and treatment evaluation. However, MRI and advanced imaging analyses by use of Artificial Intelligence (A.I.) could help to non-invasively provide more certainty about the prognosis and response to therapy, which is beneficial for treatment decision-making and counselling of the patient.

Our group aims to tackle unmet needs in the use of A.I. in the clinical setting. We focus on reproducibility and generalizability of A.I. generated outcomes, but also study the clinical impact of A.I.-generated parameters, especially regarding their relation with outcome and therapy response.

As a PhD candidate you will research the clinical impact of A.I.-software packages in clinical practice of neuro-oncology patients. You will focus on analyses of A.I.-generated, tumor-related factors for non-invasive tumor characterization. You will also investigate the potential link between tumor characteristics and patient outcome. You have access to already available datasets as well as contribute to extending relevant datasets via collaborations and (re-)use of national and international registries and biorepositories. A.I.-software packages will primarily consist out of commercially available software packages.

Tasks and responsibilities

• Collection and curation of available neuro-oncology datasets with patient demographics, biomarker data, and MRI data.
• Collection and curation of A.I.-generated, tumor-related features for available neuro-oncology datasets.
• Collaborate on collection and curation of datasets and A.I. features with international partners (Germany).
• Literature review into patient- and tumor-related factors and outcome in neuro-oncology patients.
• Implementation and benchmarking of commercial and open-source A.I. software packages aimed at outcome in neuro-oncology patients.
• The creation of alternative open-source A.I. software packages aimed at outcome in neuro-oncology patients.
• Study of methodological challenges in clinical research and optimization of implementation of commercial and open-source A.I-software packages in clinical practice.
• Performing statistical analyses of A.I.-generated tumor-related factors in relation to patient outcome.
• Reporting research findings in scientific papers and presentations at (international) meetings.
• Writing of PhD thesis.

Requirements
Specific Requirements

Our ideal candidate has a MSc degree with training in (bio)medical sciences or technical medicine and experience with various statistical techniques, including survival analyses, and software. Having experience with A.I. in research and/or clinical settings is preferred. You are a team player, accurate, good communicator and show flexibility with regard to collaborations and tasks. Moreover you have an interest in sharing knowledge and skills via teaching activities within Radboudumc curricula. You are keen to think across multiple disciplines and connect molecular to epidemiological and clinical research.

Naturally, you will receive support and training throughout the PhD trajectory to allow for development of relevant knowledge, expertise and skills.

Additional Information
Benefits

At Radboud university medical center, you build on your future. We are committed to providing the best care, education, and research. And we are true to our word, because we help you develop and seize opportunities and give you the room to grow. As an employer, we believe that employees should feel vital and happy at work in all stages of life. We are also committed to creating a healthy and safe working environment. Our employment conditions contribute to that. What we offer:

• Upon commencement of employment, you will start at scale 10A, step 0 (€2,901 based on a full-time appointment). Over a maximum period of 4 years, you will progress to scale 10A, step 3 (€3,677 based on a full-time appointment). You will also receive an 8% holiday allowance, an 8.3% end-of-year bonus, and a 47% to 72% bonus for working unsocial hours.
• Plenty of opportunities for personal development. You can take a variety of courses in our online learning environment. You can also share knowledge with colleagues through digital learning spaces – perfect for getting inspired and inspiring others.
• Your well-being and vitality are our priorities. For instance, you can enjoy a 40% discount on a sports subscription at the Radboud Sports Center along with access to the Healthy Professionals program designed to assist you in managing your energy. If you are going through a life-changing event, our Company Support Team and a personal coach are there to help you.
• Support in achieving a good work-life balance at every stage of your life. This includes advice and training courses (from ‘Millennial Dilemmas’ to ‘Your Career After 57’), activities at our own mindfulness center , and informal caregiving consultations if you have questions about juggling work and caregiving responsibilities at home.
• 168 holiday hours per year (23 days) based on a 36-hour working week.
• 26 weeks of parental leave, nine of which are paid.
• You build up a pension by ABP Pension Fund, and Radboudumc pays 70% of the pension premium.
• Discounts on health insurance and ten other types of insurance, from home insurance to legal assistance.
• An allowance for your travel expenses or a working-from-home allowance of €2 per day.

Selection process

Any questions? Or wondering what it is like to work at Radboudumc? Then call, send a message or email to Dylan Henssen , project leader. Use the Apply button to submit your application.

Additional comments

Any questions? Or wondering what it is like to work at Radboudumc? Then call, send a message or email to Dylan Henssen , project leader. Use the Apply button to submit your application.

Website for additional job details

https://www.academictransfer.com/338249/

Work Location(s)

Number of offers available

1

Company/Institute

Radboudumc

Country

Netherlands

City

Nijmegen

Postal Code

6525 GA

Street

Geert Grooteplein-Zuid 10

Geofield

Where to apply

Website

https://www.academictransfer.com/en/338249/phd-candidate-artificial-intelligenc…

Contact

City

Nijmegen

Website

http://www.radboudumc.nl/

Street

Geert Grooteplein-Zuid 10

Postal Code

6525 GA

STATUS: EXPIRED