Jobs

PhD Position in Natural Language Processing (published Jan 2020)

 

We offer a funded PhD student position in Natural Language Processing (NLP). You will join our interdisciplinary team working on applied NLP and information retrieval (IR) methods specifically adapted to large collections of scientific documents. The goal of our project is to create a novel web-based interface that makes use of NLP and IR methods to assist scientists in the exploration and assimilation of the scientific literature. In a collaborative effort, you will work on a diverse set of research problems revolving around the design of novel text embeddings, on multi-document summarization approaches, and on textual inference on citation networks.

Your background and interests ideally are in NLP, IR, computational linguistics, neuroscience, or artificial intelligence. Your have a MSc in Computer Science or a related area, are an excellent programmer, a good communicator, and a strong team player. 

To apply, send your CV, motivation letter, and MSc transcript to Richard Hahnloser (rich@ini.ethz.ch).

For some of our recent work, see: 

N. I. Nikolov, A. Calmanovici, R.H.R. Hahnloser. Large-scale Hierarchical Alignment for Data-driven Text Rewriting, Proceedings of RANLP (2019).

N. I. Nikolov, M. Pfeiffer, R.H.R. Hahnloser. Data-driven Summarization of Scientific Articles. Proceedings of the Eleventh International Conference on Language Resources and Evaluation, LREC 2018, Miyazaki, Japan (2018). Also https://arxiv.org/pdf/1804.08875.pdf

Lipkind, D., Zai, A. T., Hanuschkin, A., Marcus, G. F., Tchernichovski, O., & Hahnloser, R. H. R. (2017). Songbirds work around computational complexity by learning song vocabulary independently of sequence. Nature Communications, 8(1). http://doi.org/10.1038/s41467-017-01436-0

PhD Position in Systems Neuroscience (Published Jan 2020)

 

We have an open position for a PhD student interested in the neural basis of vocal learning. We study the brain and behavior of zebra finches with the goal of inferring the neural code of birdsong, a prime example of a highly skilled learned motor behavior. Currently, we combine diverse experimental and theoretical approaches ranging from miniature wireless sensors of vocal and respiratory dynamics (1), devices for chronic neural recordings (1,2), large-scale high-throughput microscopy (3), and manifold-based datascience (4). We are looking for a creative PhD student eager to acquire and process large data sets using state-of-art experimental approaches and who is equally interested in biological mechanisms and in applying modern machine learning techniques. We offer an exciting work environment and the opportunity to be part of a multi-disciplinary research team that has broad expertise ranging across animal communication, sensorimotor transformations, reinforcement learning, and speech and natural language processing (NLP). NLP is closely related to birdsong and our expertise in both these research areas provides opportunities for cross-fostering of ideas between biological and computational sciences. We are part of a large Swiss-wide consortium working on the evolution of language (NCCR Evolving Language http://www.snf.ch/en/researchinFocus/nccr/evolving-language/Pages/default.aspx). The ideal candidate for this position has a degree in biology, neuroscience, electrical engineering, physics, mathematics, or computer science. A strong commitment to teamwork is a top asset and crucial for a successful career in Systems Neuroscience. The Institute of Neuroinformatics is a multidisciplinary Institution affiliated with the ETH Zurich and the University of Zurich, and is located on the Irchel Campus of the University. One of the aims of the Institute is to advance our understanding of the neural strategies and representations of natural intelligence. For questions and applications, please contact: Prof. Richard Hahnloser (rich@ini.ethz.ch).