We are hiring – Autumn 2020 – NEW open jobs in explainable AI and interpretable ML

We have differnent open positions and jobs available in the field of explainable AI/interpretable machine learning (see open jobs below).

In case you are interested please
send one single e-Mail containing one single pdf file containing

  • a short motivation statement why you want to work with us;
  • your curriclum vitae (cv)
  • and the respective job code in the header of the eMail (otherwise your email will not pass)

to: a.holzinger AT tugraz.at

Note: please make sure to put into the header of your mail the respective job code in the header to make sure that the e-Mail goes through our AI filter (otherwise your message will not pass the automatic filter system). Thank you!

Our research seminar provides more relevant information:
https://human-centered.ai/hcai-research-seminar-2020/

SP.71 xAI Engineer
Status
open
Worktype
Full Time Position (minimum of two years)
Goals
You have a good knowledge of conducting usability experiments in the context of explainability/interpretability applicable for the field of digital pathology. You have professional experience in evaluation of such experiments and have good handling of data analytics and statistics tools and are also able to write a little Python skript when needed. You have a interest in AI and machine learning generally and in AI for medicine in particular and are eager to test, evaluate and validate new approaches together with end users from the clinicial domain. This requires good communication skills in both English and German. If this is a challenge for you please send your letter of motivation together with your CV and your experience via e-mail to andreas.holzinger AT medunigraz.at and put the job code SP.71-AI-2020-CSAIP into the header of your mail to pass through the filter.
Required Knowledge
Completed Doctorate, PhD, or - at least - completed Masters degree in Psychology, Cognitive Science or related field in experimental sciences
Additional Information
SP.70 Contextual pattern analysis with deep learning approaches
Status
open
Worktype
All levels
Keywords
artificial intelligence, machine learning, deep learning
Goals
You will work together with our group on histopathological Gigapixel images from our own scanning pipeline [1] and from openly available whole slide image repositories [2], [3]. Your specific tasks will include the generation of images showing concepts, simulations of different tumor gradings, and particularly the training of deep learning networks for the classification of concepts, where the challenge is on selection, experimentation of the most appropriate network structure and the size of the training task. The task depth and complexity will be adapted to the individual experience (Bachelor, Masterproject, Masterthesis, PhD, ...) Job code AI2021x10
For Students of
Computer Science, Informatics, Software Engineering, etc.
Required Knowledge
Good command of Python, Tensorflow, Colab, ... (no WEKA, no KNIME)
SP.69 Patterns of Explainability
Status
open
Worktype
All levels
Keywords
Artificial Intelligence, Explainable AI, medical AI, decision making research
Goals
The goal is to design, develop and evaluate a reference model of explainability in order to combine findings from both machine intelligence and human intelligence [1]. The candidate will at first analyize the state-of-the-art and then carry out an empirical study on medical decision making tightly connected in a team within the Human-Centered AI Lab. In the empirical study you will make use of prior results in formal modeling of clinical decision making in digital pathology [2]. Based on the empirical studies you will develop a library of explanatory patterns and a grammar of explainations on how these can be combined.
For Students of
Computer Science, Informatics, Software Engineering
Required Knowledge
Interest in experimental research, Analyzing and observing medical workflows, Analytical thinking, Evaluation of experiments
Abstract
Details of the project and payment opportunities will be discussed in a personal meeting.
Reading
If you are interested in doing your Bachelor, Masterproject, Masters in this area please drop an eMail to a.holzinger AT tugraz.at and include a) a short motivation note why you want to carry out this work b) your CV Please put SP.69 21W2020Y in the header of your email so that the mail passes the automatic mailfilter system. Thank you for your kind interest.
SP.68 Frontend Developer
Status
open
Worktype
Frontend Developer (all levels)
Goals
Reinforce our research team with desiging, developing and testing clear front end architectures with good performance and good usability within our research projects useable for medical domain experts. Join our Lab team working with most modern program methodologies such as extensive code reviews, pair programming, daily standups, (unit) testing, clean code, continuous integration and deployments. Work together with our young vibrant team in a cool Lab research atmosphere on challenging tasks in international projects. With your contribution you actively shape the functionality of our projects
Abstract
Ideally you are experienced in the Javascript ecosystem covering React, Angular, Vue, Flow, or Typescript. Understanding complexities of managing vast application state, orchestrating action chains and dealing with upcoming side effects. If you are interesting send an e-Mail containing your experience and CV and do not forget to put the reference number WP68FD2021x10 into your mail-header.
SP.67 Human-AI Interface DESIGNER
Status
open
Worktype
Human-AI Interface Designer
Goals
In close cooperation with the Human-Centered AI research team you will design sophisticated advanced human-ai interface concepts for our research projects in the medical domain and test these protoypes in the field of explainable AI, Q/A systems and Counterfactual reasoning.
Abstract
Ideally you are a creative and innovative designer who likes to experiment with novel ideas and like to test these prototypes in the medical domain to create amazing user experiences. You should have a feeling for clean and artful design, having good UI skills and are able to transform high-level requirements into interaction flow and test these in various scenarios. Do not forget to put the job code into the header SP67HAI2021x10
SP.66 Python nerds
Status
open
Worktype
Paid Bachelor Theses, Master projects, Master theses
Keywords
Explainable AI and interpretable Machine Learning
Goals
Tasks include: - Data pre-processing (Whole Slide Images) - Algorithm implementation - Experimental work - Collaboration within an international team - Collaboration with medical professionals - Excellent programming skills (e.g. Python) - Very good written and spoken English Bachelor theses (706.170, 706.171, 706.172 etc.) Master projects (706.501, 706.502, 706.505) Master theses (706.997, 706.998) JobCode: SP662021x10PY
For Students of
Computer Science, Informatics, Software Engineering, etc.
Required Knowledge
For our R&D projects we are expanding our group with persons interested in xAI methods, Causability, meta-learning, variational autoencoders, caption generation and object detection, with a keen interest in medical image processing

Contact: a.holzinger AT tugraz.at

https://human-centered.ai/open-positions/

The Human-Centered AI Lab (Holzinger group) is following the principle: “Science is to test crazy ideas – Engineering is to put these ideas into practice” and dedicated to contribute to the international research community towards ethical responsible machine learning for the support of human health.