Are you a currently enrolled student at the Master or PhD level with a strong 
interest in Deep Learning, Reinforcement Learning, and/or NLP?
 
NAVER LABS Europe is opening an internship position on Reinforcement Learning 
for Controlled Text Generation, which might be of interest to you. 
 
For more information and for applying, please visit the link below:
https://europe.naverlabs.com/job/reinforcement-learning-for-controlled-text-generation/
 
 
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NAVER LABS Europe: Internship  
 
Start date: Fall 2019 or early 2020
Duration; 5-6 months
 
We are opening a research internship on Reinforcement
Learning techniques for applications to controlled text generation.
Under conditions where training data is limited, standard end-to-end
training of seq2seq models may generalize poorly and produce
inadequate results at test time. A possible remedy is to augment
models with rewards that control the quality of the outputs. These
rewards can address two complementary goals: (i) taking into account
global characteristics of observed sequences that go beyond standard
local teacher-forcing training techniques (observation bias problem),
and (ii) moving the generation process towards desired properties of
the output (e.g. favoring shorter sentences or performing style transfer).
 
Supervisors: Marc Dymetman and Hady Elsahar.
 
We are looking for a motivated intern to help us develop methods and
algorithms for addressing this general problem, both in theory and in
practice. Experiments will be conducted on selected text generation
tasks (NLG, Summarization or Machine Translation).
 
The successful candidate should be enrolled in a graduate program, at
the Master or (preferably) PhD level, with experience (ideally) in
Deep Learning, Reinforcement Learning and Natural Language Processing.
 
Publication of results in major conferences/journals will be strongly
‚Äčencouraged.
 
REQUIRED SKILLS :
Strong mathematical and programming skills as well as familiarity with one of 
the major current deep learning toolkits
(PyTorch preferred but not compulsory) are a requirement. 
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