Two open PhD positions at LMU Munich, NLP and Deep Learning

Two open PhD positions at LMU Munich, NLP and Deep Learning
Duration: 3 years - Starting date: Immediate
PhD 1: Argument validation
The topic of the project is validation of arguments
(extracted from text) using machine learning methods, in
particular deep learning methods. This position is funded
by the DFG program SPP 1999 Ratio, a network of ten projects
across Germany conducting research on "Robust Argumentation
Machines". Three partners are involved in the LMU
subproject: LMU's NLP group (CIS), LMU's database group
(DBS) and Siemens Corporate Technology.
PhD 2: Neural architectures for representation learning
This position is funded by the European Research Council
Advanced Grant NonSequeToR. The topic is developing neural
architectures for learning the next generation of
representations for NLP. Topics include tokenization-free
representation, multitask learning and robust cross-lingual
methods.
Candidate
Ideal candidates have a master in computer science or a
related discipline, a strong interest in natural language
processing and machine learning, excellent programming and
mathematical skills and are team players and fluent in
English.
Team
The Center for Information and Language Processing (CIS) at
LMU is headed by Hinrich Schütze and is internationally
recognized for its research on statistical natural language
processing and deep learning for natural language
problems. We are a growing team of 20+ PhD students and
researchers. LMU is the top university in Germany according
to most rankings.
Terms and conditions
We offer a one year position that will be extended to three
years after a positive evaluation.
Diversity
LMU is strongly committed to diversity and especially
welcomes applications from members of underrepresented
groups.
Application
Please send CV, transcripts, names of two references and a brief
motivation letter stating your research interests, past experience and
which position you are applying for to "jobs-AT-cis.lmu.de" . All documents
should be sent as a single PDF. The two positions are open until
filled.