[visionlist] job advertisement | 1 fully funded PhD position (E13) | Application deadline: Nov.18, 2024

[Heiko Neumann]

Vacancy for dissertation/PhD project
*Learning Search and Decision Mechanisms in Medical Diagnosis*

We are looking for a new PhD student for a fully funded 
interdisciplinary research project investigating the computational 
mechanisms underlying the perceptual processes in medical imaging.

*Brief project description and goals*
Medical experts routinely screen images for signs of abnormality 
indicative of a disease. Experimental evidence shows that these experts, 
based on their training, are able to make a diagnose above chance level 
even after screening images for only a few seconds. Such visual 
inspection utilizes global ensemble scene statistics, or “scene gist”, 
to provide contextual guidance information.

The goal of the PhD project is to investigate how such global, 
contextual gist information can be computed and incorporated in machine 
vision approaches, such as deep neural networks for natural or medical 
image processing. In particular, a goal is to develop neural mechanisms 
that can be integrated into existing pre-trained CNNs to compute scene 
gist for rapid global decision-making and contextual guidance in medical 
images. Such mechanisms should explain how such global feature 
compositions are learned to increase the classification specificity and, 
at the same time, do not equip an observer with the ability to precisely 
localize such feature compositions indicative of the evidence. At the 
implementation level, computational units (neurons) in hierarchical CNN 
architectures will be extended by integrating local bottom-up feature 
extraction mechanisms with top-down modulatory contextual fields. We 
focus on these mechanisms to learn the integration of information 
streams in counter-stream networks by employing novel two-point 
information integration units inspired by recent findings from 
neuroscience. These investigations will contribute to develop novel CNN 
architectures by integrating feedforward and feedback data streams that 
operate at different spatio-temporal scales and feature types inspired 
by computational mechanisms in biological vision. The combined global 
and local information is expected to provide more detailed explanations 
on a mechanistic level how radiologists steer their attention and search 
capacities and learn to improve such skills.

*Requirements*
- MSc degree in Computer Science, Engineering, Physics, Mathematics, 
Cognitive Systems/Science or equivalent relevant background
- Experience in computational vision, neural networks, machine learning; 
with strong mathematical/physics foundation
- Experience in developing biologically inspired models – or interested 
in learning how to develop such mechanisms and models
- Experience in analysis of large data and evaluation of results
- Strong coding skills
- Personal skills: working in a team, but should be able to work 
independently, is strongly focused and enthusiastic about the project 
theme, is self-motivated and takes responsibility for reaching milestones
- Experience and talent in scientific writing (with proficient written & 
oral English)

*Contact & application*
The project is part of the newly founded research training group “KEMAI” 
that focuses on integrating knowledge and learning based approaches for 
better medical AI (https://kemai.uni-ulm.de/ for more information). The 
offered PhD position is fully funded (E13 salary) and also benefits from 
an interdisciplinary setting, the ability to connect with peers from 
related projects and a clearly structured PhD program.

Application materials are expected until November 18, 2024. They should 
contain a CV, statement of research interest and background in relation 
to the KEMAI training group and project theme C2. A cover letter should 
inform about the expected date of availability and name of two referees. 
Submit your application via the KEMAI website (preferred) or to Prof. 
Heiko Neumann (heiko.neumann at uni-ulm.de) or reach out for more information.


-- 

Prof. Heiko Neumann
Institute of Neural Information Processing
Faculty of Engineering, Computer Science and Psychology
Ulm University
James-Franck-Ring
D-89081 Ulm
Germany

phone:  +49 (0)731 50 - 24158
         +49 (0)731 50 - 24151 (secr.)
fax:    +49 (0)731 50 - 24156
email:  heiko.neumann at uni-ulm.de