[jobs] Two fully funded PhD positions in Machine Learning at Orebro University (Sweden)

[Todor Stoyanov]

# Two fully-funded PhD. student positions in machine learning

## Meta-reinforcement learning (4 years):

The topic for this position is meta-reinforcement learning (RL) for
transfer learning (TL) in reinforcement learning and entails fundamental
research on (deep) TL and meta-RL. For this project, we will investigate
methods for fast and efficient RL in real-world settings by exploiting
knowledge transfer, e.g. from other domains or experience, to allow
faster learning in the target environment. Research in this project will
be performed in close collaboration with other PhD. students and
post-docs in the same research environment.

* Prior knowledge, experience, and interest in reinforcement learning in
continuous spaces and deep learning are expected for this positions.
* Prior knowledge, experience, and interest in robotic perception and
control are advantageous.

<https://www.oru.se/english/working-at-orebro-university/jobs-and-vacancies/job/?jid=20200265>

## Interpretable and statistical continual learning (4 years):

The topic for this position is continual learning for dataset shift and
entails fundamental research on data efficient and interpretable models
and algorithms. For this project, we will investigate methods for
learning, updating, and forgetting for domains where data is
incrementally available or changes over time. Research in this project
will be performed in close collaboration with other PhD. students and
post-docs in the same research environment, as well as external
collaborators with Cambridge University.

* Prior knowledge, experience, and interest in probabilistic machine
learning, statistical learning, Gaussian Process, and probabilistic
graphical models are expected for this positions.
* Prior knowledge, experience, and interest in Bayesian methods and deep
Gaussian processes are advantageous.

<https://www.oru.se/english/working-at-orebro-university/jobs-and-vacancies/job/?jid=20200266>

## How to apply

For pre-application inquiries please contact Johannes A. Stork
(johanne...@oru.se) or Todor Stoyanov (todor.s...@oru.se).
Application is only possible via the online application service (see
links above). Application by e-mail is not possible.

## What we offer

Four year fully funded employment to do fundamental research on exciting
topics and within a dynamic research  environment. We are looking for
exceptional students interested in meta-reinforcement learning and
continual learning to join our newly started research group
(<https://amm.aass.oru.se>). We are particularly interested in
applicants with a strong background in computer science, machine
learning, robotics, and mathematics. The positions are funded through
the Wallenberg AI, Autonomous Systems, and Software Program (WASP). The
PhD. students will belong to the graduate school within WASP
(<https://wasp-sweden.org/graduate-school/>). Applications will be
considered immediately and up to the application deadline of 2020-09-30.
Expected start of employment: no later than 1st January 2021.

## The successful candidates should have:

* Master of Science degree in computer science, machine learning,
robotics, or a related field
* Motivation to obtain a doctoral degree
* Strong mathematical background
* Prior research experience in the areas of machine learning or robotics
* Programming skills
* Excellent communication skills in English

--
Todor Stoyanov
Associate Professor
Autonomous Mobile Manipulation Lab,
AASS, Orebro University
https://amm.aass.oru.se/people/todor-stoyanov/
--

[Gari Clifford]

# Two postdoctora research positions in machine learning applied to 

large-scale neuropsychiatric data and cardiovascular data

1. Multimodal ML for Neuropsychiatric data:  

This position involves the integration of neurological and 

audio-visual data to determine and predict changes in cognitive state.

As part of a $50 million 5 year project, the candidate will interact with 

clinical experts, architects, HCI experts and ML experts, collaborating 

on large quantities of heterogenous data types collected continuously 

in both home and a purpose-built hospital environment. 

2. Spatiotemporal ML for Cardiovascular data:  

This position involves working on multidimensional signals, images 

and videos for cardiovascular diagnoses. With access to over 

60 million recordings, this position requires the development of 

novel ensemble and noisy label approaches for boosting classifier

and prediction performance. 

## The successful candidates should have:

* Prior knowledge, experience, and interest in multimodal machine
learning, deep learning and computer vision are expected for position 1.
* Prior knowledge, experience, and interest in machine learning,
and spatiotemporal deep learning are expected for position 2.

* PhD in computer science, machine learning, information engineering, 

  statistical signal processing, physics, mathematics, or a related field.
* Strong programming skills.
* Strong written and oral communication skills in scientific English.

* Prior knowledge, experience, and interest in adversarial networks,
attention modeling, and noisy label learning are advantageous.

* Familiarity with computing in AWS and GCP also advantageous.

## Environment:
The successful candidate will join a core team of 2 research assistant professors, 

4 postdocs, 5 research engineers and 10 PhD students from Georgia Tech's

ML and Engineering PhD programs, and from Emory's Computer Science 

& Informatics PhD. The wider collaborative teams constitute around 100

researchers.  The team is spread across research space located on both campuses

on the 15th floor of Georgia Tech's Coda High Performance Computing Building 

in the heart of 'Tech Square', and on the 4th floor of the Woodruff Memorial 

Research Building, adjoined to Emory University Hospital. 

Both spaces have been recently (re)constructed to create state-of-the-art

collaborative spaces with the best coffee machine in Atlanta. 

With strong ties to industry and philanthropy, resources are excellent and

career prospects are strong. You will be mentored to join world class companies

or institutions, with former researchers now at MIT, Harvard, The Technion, 

Oxford, Google, AWS and other prestigious organizations. There are also

opportunities for involvement in early stage startup companies with 

significant backing. 

## How to apply

For pre-application inquiries please contact Gari Clifford at:
chair [at] dbmi . emory . edu

To apply, email a CV and covering letter with your career

aspirations and availability for interview and commencing 

employment at: bmi-jobs [at] dbmi . emory . edu

---

Gari. D. Clifford,  

Chair, Dept. of Biomedical Informatics, Emory University

Prof. of Biomedical Informatics & Biomedical Engineering

Dept. of Biomedical Informatics, Emory University

Dept. of Biomedical Engineering, Georgia Institute of Technology & Emory University