The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing and machine learning. Applicants must have a Ph.D. in a relevant discipline and a strong research record.

The center has a number of postdoctoral positions available. Application instructions for each position are described below.

If you are applying for multiple positions to the email clspsearch@clsp.jhu.edu, you only need to send one email. You will be considered for all applicable positions.

• Trend Detection in Social Media
  Collaborators: Mark Dredze (mdredze@cs.jhu.edu), Benjamin Van Durme
  Trends embedded in large streams of social media have been shown to
  capture important population information across a number of
  applications, including political polling, product sentiment, disaster
  response and public health. This project will investigate these and
  other applications by developing new machine learning and NLP
  algorithms for mining social media data.
  Deadline: Applications will be accepted until positions are filled.
  Application instructions: Interested applicants should contact clspsearch@clsp.jhu.edu, and include a CV and 3 recommenders who can supply letters on request. Please reference this position in the subject line.
• Analysis of Clinical Medical Text
  Collaborators: Mark Dredze (mdredze@cs.jhu.edu)
  Extracting information about patients from medical records can help
  improve treatments, and identify important trends in a patient
  population. Much of this information is contained within clinical
  texts. This project will investigate information extraction tools for
  the extraction of structured information from clinical free text.
  Deadline: Applications will be accepted until positions are filled.
  Application instructions: Interested applicants should contact clspsearch@clsp.jhu.edu, and include a CV and 3 recommenders who can supply letters on request. Please reference this position in the subject line.
• Topic Identification and Analysis from Text
  Collaborators: Mark Dredze (mdredze@cs.jhu.edu), Benjamin Van Durme
  The identification of core topics in a document has broad downstream
  applications, including improving information retrieval systems,
  machine translation and information extraction. Many times these
  topics are unknown ahead of time, but must be discovered and learned
  from a new corpus of documents. This project will investigate new
  methods for topic identification and classification, including topic
  models and document classification methods.
  Deadline: Applications will be accepted until positions are filled.
  Application instructions: Interested applicants should contact clspsearch@clsp.jhu.edu, and include a CV and 3 recommenders who can supply letters on request. Please reference this position in the subject line.
• Broadly Multilingual Learning of Morphology and Low-Resource Machine Translation
  Collaborators: David Yarowsky, Jason Eisner, Sanjeev Khudanpur
  We are seeking several postdocs starting in 2017 to work on a wide range of problems in computational morphology and machine translation of over 800 low-resource languages. We will address a very large and diverse set of world languages using a broad spectrum of approaches, over large annotated and unannotated datasets of both text and speech. Computational linguists, formal morphologists and specialists in machine translation and machine learning of human language are all welcome.
  Deadline: Applicants should apply by March 6, 2017 for full consideration, but applications will be accepted until positions are filled.
  Application instructions: Interested applicants should contact David Yarowsky <yarowsky@jhu.edu>, including a statement of interests, CV, research statement and either 3 letters of recommendation or names and contacts of 3 referees who can supply letters on request. Please reference this position in the subject line.
• NLP and Machine Learning for Clinical Data Analysis
  We are seeking a candidate to work with The Johns Hopkins Center for Population Health IT (CPHIT) in the field of health informatics, computer science applied to health care and public health. The candidate will have the opportunity to work closely with health informatics, computer science, methodologies, public health and medical faculty undertaking a wide array of information science related projects focusing on the application of electronic health records, electronic health care administrative records, and consumer e-health/m-health data applied to the improvement of health care systems, public health agencies and programs that target the “population health” of communities and target consumer groups. We are seeking someone with a doctoral level degree and advanced training and/or experience in a data/information science discipline. Ideally, the candidate will have extensive experience working with digital health or health care data. Familiarity with the US health care system is preferred.The position can start July 2017 or earlier. The position is for one year, though extensions may be possible.
  Deadline: Applications will be accepted until the position is filled.
  Application instructions: Send CV and cover letter to Elyse Lasser.
  More Information: PDF

Johns Hopkins University is a private university located in Baltimore, Maryland. The campus provides easy access to a number of affordable and vibrant neighborhoods and waterfront dining options. Hopkins is also connected to Washington DC (40 mins), Philadephia (1.5 hours) and New York city (2.5 hours) via direct trains and buses.

CLSP has a history of placing students in top academic and industry positions, with a large network of alumni at Google, Amazon, Microsoft Research, IBM Research, Facebook, Twitter, Nuance, BBN, and numerous startups.

Applicants are not required to be to US citizens or permanent residents.

Questions about specific projects should be directed to the contact information associated with the project. General inquiries may be sent to clspsearch@clsp.jhu.edu.