Computational Linguistics Research Scientist/NLP
Company : Leidos
Country: United States
Location : Bethesda, Maryland
Post: Wed, 01 Feb 2023 20:33:23 GMT
Expires: Wed, 01 Mar 2023 23:59:59 GMT
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—————————— Job Description ——————————
The Leidos Innovation Center (LInC) Advanced Analytics team has an opening for a Computational Linguistics Senior Research Scientist with a background in designing Natural Language Processing (NLP) and Human Language Technology (HLT) approaches that integrate, adapt, and extend novel capabilities to address the customer’s research challenges in competitive contract and internal research and development (R&D) programs (basic and applied). Candidates with a deep technical background in computational linguistics, human language technology, machine translation, automated speech recognition, machine translation, linguistic data analysis, statistical programming, data science, are strongly encouraged to apply.
We are looking for a senior scientist with a specialization in NLP research to work with PhD-level peers to develop and implement approaches and solutions for contract research and development projects. The innovative technical approaches and solutions delivered to customers that advance the state of the art in the research while addressing long-term problems of importance to national security. We are seeking individuals knowledgeable in various text processing, data curation, and linguistic annotation methods, as well as familiarity with state-of-the-art research in natural language processing and practical application of related machine learning methods to human language data. Experience constructing corpora, adapting/tuning NLP models, and evaluating natural language processing technologies in an operational environment is a plus. The ideal candidate will have a proven track record of supporting all aspects of the program life cycle: supporting business development through the design of new research concepts and topics; writing technical approaches and plans as part of the proposal process; leading multi-discipline project teams and supporting project execution objectives; and transition of impactful, novel capabilities to stakeholders and the communities of practice at the project’s conclusion.
Independently influence the development of approaches and solutions that address highly-complex research challenges as well as partner in a team environment across organizations.
Independently design and undertake new applications of NLP research as well as partner in a team environment across organizations.
Develop topics for novel and innovative R&D approaches to solving challenges in the area of NLP and work with potential sponsors (customers or internal champions) to secure funding for new research efforts based on those topics.
Collect, curate, and analyze natural language corpora for a variety of NLP and text analytic tasks.
Perform metrics-based evaluations of new technologies from research organizations to determine potential contributions.
Lead teams of fellow researchers, data scientists, data engineers, and software engineers to execute complex R&D programs.
To be successful in this role you need these skills (required):
Advanced degree (PhD highly desired) in computational linguistics, computer science, data science, or a related discipline, such as statistics or applied mathematics.
Demonstrable experience (both individually and leading/directing others in) adapting and extending open technologies in the context of novel approaches for NLP tasks. Tasks of interest include: computational linguistics, text analytics (to include data from multilingual sources), speech recognition, machine translation, formal grammar, lexical semantics/semantic parsing, coreference analysis, discourse analysis, argument mining, lexical entailment, natural language understanding, natural language generation, and multi-role dialogue understanding.
With a Master’s degree, at least thirteen (13) years of specialized experience innovating analytical techniques and performing analytical functions using machine-learning libraries or other approaches. With a PhD, at least ten (10) years of specialized experience is required.
Experience in the following areas: text processing and construction of corpora in unfamiliar languages; processing of large text collections with standard NLP tools for parsing, entity extraction, POS tagging, topic discovery and classification (such as sentiment analysis), and natural language understanding; tuning hyper-parameters of existing NLP models for domain-specific data sets; computational manipulation and analysis of natural language documents using statistical models; experimenting with large corpora for developing and testing advanced NLP algorithms.
Ability to program in Python, Perl, or other scripting language.
Familiarity with common NLP and ML toolkits such as Stanford CoreNLP, OpenNLP, NLTK, scikit-learn, and Tensorflow.
Knowledge of state-of-the-art methods coupled with the creativity and intelligence to advance beyond them. Track record of active learning and creative problem solving.
Track record of relevant publications in peer-reviewed conferences and journals.
Experience leading technical projects to successful completion.
An active DoD Secret Security clearance with the ability to upgrade to a TS/SCI w/ Polygraph
Previous experience as a technical lead, such as a principal investigator on a project
Experience as a PI on projects for a competitive contract R&D customer, such as DARPA
Familiarity with collaboration environments (e.g. Jupyter notebooks, PyCharm)
Prior experience with many of the following models: Deep Learning (CNNs, RCNNs, LSTMs), GANs, Autoencoders, Reinforcement Learning, Siamese Networks, Logistic Regression, Linear Regression, Support Vector Machines, Hidden Markov Models, Conditional Random Fields, Latent Dirichlet Allocation
Pay Range $(phone number removed) – $(phone number removed) – $(phone number removed)
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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