A Staff Scientist position is currently available in Dr. Ivan Ovcharenko's group within the Intramural Research Program of NIH/NLM. The group is actively seeking an outstanding candidate to conduct research in the machine learning area of human regulatory genomics. The candidate will develop state-of-the-art deep learning methods for the accurate prediction of enhancers and silencers, identification of disease-causative mutations, and reconstruction of cell-type specific regulatory architecture of the human genome. This position is responsible for:
- developing machine learning methods, including deep learning methods;
- performing statistical analyses, devising new computational methods, and creating analytic models;
- analyzing large genomic and epigenetics datasets;
- working in collaboration with other experimental and computational laboratories at the NIH;
- publishing scientific manuscripts and presenting at conferences and meetings;
- mentoring students and postdoctoral fellows; and,
- staying abreast of bioinformatics and deep learning methods as well as genomic resources.
Salary is commensurate with research experience and accomplishments. A full package of benefits, including retirement, health, life, and long-term care insurance, Thrift Savings Plan participation, etc., is available. The successful candidate will serve in a non-competitive appointment in the excepted service.
DHHS, NIH, and NLM are Equal Opportunity Employers
The ideal candidate may or may not be a United States citizen and must have a PhD degree. We are looking for an individual with several of these qualifications or talents:
- a Ph.D. in a quantitative field, such as Computer Science, Mathematics, Computational Biology, or Bioinformatics;
- at least two years of relevant postdoctoral experience;
- a strong track record in research as evidenced by peer-reviewed publications;
- research experience in regulatory genomics, computational disease genetics, and/or genomic and epigenomic architectures of cellular identity;
- experience developing deep learning algorithms, methods, and tools;
- ability to communicate effectively, both verbally and in writing; and
- ability to work both independently and as a team member.
Interested individuals should send a copy of their CV and Bibliography with the names of three references along with a cover letter detailing research interests, a brief summary of communication and organizational skills, and evidence of engagement in multi-disciplinary collaborative research to firstname.lastname@example.org. Please include the announcement number, NLM27-0015, in the cover letter. Applications will be accepted until the position is filled.