Assistant Researcher- Neuroscience - Helen Wills Neuroscience Institute
The Helen Wills Neuroscience Institute (HWNI) at the University of California, Berkeley, invites applications for an Assistant Researcher in the area of Neuroscience. This individual will be accountable for the development and application of machine learning algorithms to extract information from large-scale neural recordings, with special attention to the specific experimental conditions in which signals were recorded, the biophysical processes from which the signals arise, and the interpretation of these signals with respect to the animal's behavior.
The primary responsibilities of the neuroscientist in this position will include developing methods for analyzing high-dimensional neural recordings to address research questions, and how behavioral information is encoded in local field potentials.
The responsibilities are not limited to the following:
(i) Ability to design, develop and assess software tools for analyzing neural recordings using unsupervised learning methods, such as sparse coding and nonnegative matrix factorization.
(ii) Ability to collaborate with project collaborators, experimental neuroscientists providing recording data and specific research questions the software tools should address.
(iii) Must be able to help manage and oversee the NIH R01 project Building Analysis Tools and a Theory Framework for Inferring Principles of Neural Computation from Multi-Scale Organization in Brain Recordings.
Basic Qualifications (required at the time of application):
The individual should have a Ph.D. degree or equivalent international degree.
Additional Qualifications (required by start date):
At least a minimum of 5 years of computational and neuroscientific data experience.
Training in neuroscience, and computational methods.
Seasoned in electro-neurophysiology, local field potentials, parametric and nonparametric statistics, and neural computation.
Experienced with the development and application of machine learning algorithms to extract information from large-scale neural recordings, and experimental conditions in which signals can be recorded; as well as interpreting the biophysical processes of signaling, and the interpretation of these signals with respect to the animal's behavior.
Acclimated to analyzing large-scale neural recordings, and is well versed in both the computational and neuroscientific knowledge.
Attention to details and strong communication skills verbally and written.
This position reports to Dr. Friedrich (Fritz) Sommer. The anticipated start date is February 03, 2020. This position is full-time (100%) and will be open until filled. The initial appointment will be for one year, with a possibility of renewal. Extension of the appointment is subject to performance and availability of funds.
Salary will be commensurate with experience.
Benefits, consist of medical, dental, and vision coverage which is included in the compensation package. To learn more about UC Berkeley's benefits offered go to https://hr.berkeley.edu/compensation-benefits/benefits
To apply, please go to the following link: https://aprecruit.berkeley.edu/JPF02455
Applicants should provide contact information for a minimum of two references. Letters of reference are not required at this time. We will seek your permission before contacting your references. All letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality (http://apo.berkeley.edu/ucb-confidentiality-policy
) prior to submitting their letters.
Feel free to address inquiries specific to this position to Dr. Fritz Sommer at email@example.com
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct