3y PhD position Machine Learning for Medical Diagnostics

10 Feb 2025
Job Information

Organisation/Company

University of Oldenburg

Department

School of Medicine and Health Services

Research Field

Computer science

Researcher Profile

First Stage Researcher (R1)

Positions

PhD Positions

Country

Germany

Application Deadline

2 Mar 2025 - 23:59 (Europe/Berlin)

Type of Contract

Temporary

Job Status

Part-time

Hours Per Week

29.85

Offer Starting Date

15 Apr 2025

Is the job funded through the EU Research Framework Programme?

Not funded by a EU programme

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

No

Offer Description

The School VI of Medicine and Health Sciences comprises the fields of human medicine, medical physics and acoustics, neurosciences, psychology and health services research. Together with the four regional hospitals, School VI forms the University Medicine Oldenburg. Furthermore, the university cooperates closely with the University Medicine of the University of Groningen.

The Division AI4Health lead by Prof. Dr. Nils Strodthoff aims to fill one PhD-position (m/f/d) for 3 years(E 13 TV-L, 75 %) at earliest convenience.

In the AI4Health division, methodological questions in the areas of self-supervised/label-efficient learning and explainability of deep neural networks (XAI) are being developed, particularly for use in biomedical applications. Further information about the department can be found at https://uol.de/en/ai4health

The position is part of the intramurally funded profile initiative "University Diagnostics Center", which aims to enable the diagnostic disciplines (University Institute for Clinical Chemistry and Laboratory Medicine, University Institute for Medical Genetics, University Institute for Medical Microbiology and Virology, University Institute for Diagnostic and Interventional Radiology, and the Division of Immunology) of the University Medicine Oldenburg to perform analyses using machine learning methods and to establish multimodal prediction models in research, teaching, and patient care in the long term.

The advertised position aims to develop data-driven prediction algorithms in the context of various diagnostic disciplines. In a first step, prediction models for single modalities are to be developed for selected use cases. In a second step, different modalities are to be combined to demonstrate the feasibility of multimodal predictions. The focus of the advertised position is on data from laboratory medicine, immunology, and microbiology. 

The project has a strong interdisciplinary character and requires, in addition to prior knowledge in the field of machine learning, an enjoyment of interdisciplinary collaboration with experts from different diagnostic application areas, learning about different data modalities, and selecting and adapting suitable learning algorithms. Research results of both methodological and applied nature should be published in professional journals and presented at relevant conferences. 

The position involves teaching duties of up to 3 teaching hours per week during the semester. There is the possibility of personal scientific qualification (doctorate).

Where to apply

E-mail

bewerbungen-vf@uol.de

Website

https://uol.de/en/job/wissenschaftlicher-mitarbeiterin-58-397

Requirements

Research Field

Computer science

Education Level

Master Degree or equivalent

Skills/Qualifications

Required qualifications:

• Completed academic degree (Diploma [University]/Master's) in computer science, physics, mathematics, or related fields
• Comprehensive theoretical knowledge in machine learning, particularly deep learning, as well as extensive practical experience in training neural networks (demonstrated through personal projects)
• Strong proficiency in the Python programming language and either extensive experience with the machine learning framework PyTorch or extensive experience with state-of-the-art classical Machine Learning algorithms, e.g., gradient-boosted decision trees (please provide evidence)

Specific Requirements

Preferred qualifications:

• Experience in medical-diagnostic application fields, ideally in fields mentioned in the task description, demonstrated through completed courses or personal projects
• Proven experience in interdisciplinary communication
• Experience with scientific presentations and publications
• Knowledge of German

Languages

ENGLISH

Level

Excellent

Research Field

Computer science

Years of Research Experience

1 - 4

Additional Information
Benefits

• Payment in accordance with collective bargaining law (special annual payment, public service pension scheme, asset-related benefits) incl. 30 days annual leave
• Support and guidance during your onboarding phase
• A family-friendly environment with flexible working hours (flexitime) and the possibility of pro-rata mobile work
• Benefits from the university's health promotion programme
• An extensive and free further education programme as well as programmes geared toward the promotion of early career researchers (https://uol.de/en/school6/early-career )

Selection process

The University of Oldenburg is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. In accordance to § 21 Section 3 NHG, female candidates with equal qualifications will be preferentially considered. Applicants with disabilities will be given preference in case of equal qualification.

Work Location(s)

Number of offers available

1

Company/Institute

Carl von Ossietzky Universität Oldenburg

Country

Germany

City

Oldenburg

Postal Code

26129

Street

Ammerländer Heerstr. 140

Geofield

Contact

City

Oldenburg

Website

https://uol.de/en/ai4health

Street

Ammerländer Heerstr. 114-118

Postal Code

26129

E-Mail

nils.strodthoff@uol.de

STATUS: EXPIRED

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