WORK TO BE PERFORMED
This position involves data analysis/modeling of foraging behavior and self-initiated movements in rodents, related to a Systems Neuroscience experiment addressing the following question.
When interacting with a complex environment, animals generate naturalistic behavior in the form of action sequences. To analyze and classify such behavior from video recordings is a computationally demanding task, requiring development of specific software pipelines adapted for big data structures using deep learning methods and state space models. This project aims at creating such a pipeline for analyzing videos of mouse behavior previously collected in the Mainen Lab at the Champalimaud Center for the Unknown, Portugal. In the experiment, animals performed certain action sequences, with variable onsets timing, leading to a water reward. Optogenetics photostimulation of inhibitory neurons in secondary motor regions was also performed during selected action sequences. Behavior during this task was recorded with two high speed, high resolution cameras pointing at the animal's face and front limbs. The large size of the datasets generated in this experiment (~1 Tb per animal, for 10 animals) requires an extensive effort to classify behavioral motifs. In the second part of the project, behavioral motifs will be related to large scale recordings of neural activity from Neuropixel probes. The fellow will investigate the relationship between neural activity and behavior using state space models and mechanistic models based on recurrent neural networks.
The fellow will integrate a dynamic team of researchers as part of a collaboration between the Mainen Lab at the Champalimaud Centre for the Unknown and the Mazzucato Lab at University of Oregon. National, foreign and stateless candidates can develop the proposed work remotely where team interaction is supported by online platforms (e.g. slack, zoom, etc).
Recanatesi, S. et al., biorxiv (2020).
Vertechi, P. et al., Neuron (2020).
Murakami, M. et al., Neuron (2017).
Murakami, M. et al., Nat. Neuro (2014).
PROFILE OF CANDIDATES
- PhD in Neuroscience, Cognitive Science, Biology, Experimental Psychology, Engineering or other areas relevant to neurophysiology and animal behavior;
- Proficiency in Python and Matlab programming language and familiarity with object oriented programming;
- Familiarity with Artificial Intelligence software (TensorFlow);
- Familiarity with data analysis of biological experiments;
- Ability to work independently and troubleshoot technical issues;
- Good capacity and value for teamwork and communication skills;
- Fluency in English.
The monthly remuneration to be attributed is the 33rd level of the single remuneration table (TRU), approved by Portaria nº 1553-C/2008, of December 31st, updated by Decreto-Lei n.º 10-B/2020, of March 20th, starting at a base gross salary of 2.134,73 Euros.
EVALUATION AND SELECTION PROCESS
The candidate’s selection will fully observe all applicable legislation and will consist in the evaluation of the scientific and curricular backgrounds of the candidates, with particular attention given to the relevance, quality, actuality and adequacy of the aforementioned backgrounds, to be weighed as follows:
- motivation letter: 15%;
- curriculum vitae: 70%.
Evaluation scale: Each application will be evaluated by the jury in a scale from 0% (not adequate) to 85% (excellent). Should there be a draw, reference letters shall be requested (5%), candidates will be invited to interview (5%) and it shall also be evaluated the potential contribution of the candidate to the ongoing Lab's research and integration in the team (5%).
Evaluation methodology: Final evaluation will be based on the above-mentioned criteria. In the event of equal score between the top candidates, the jury will interview each candidate, the result of such interview to serve as the sole tie-breaker.
Based on the above, candidates will be ranked to reflect their global evaluation. A meeting minute will record each jury meeting.
COMPOSITION OF THE JURY:
Chair: Zach Mainen;
Member: Fanny Cazettes
Member: Catarina Pimentel;
Alternate member: Cindy Poo
Applications will be accepted until June 15th, 2020 or until a qualified candidate is hired. Candidates must submit a single document (maximum 4 pages; paper or PDF file) that contains a motivation letter and the Curriculum Vitae, both written in English.
Email applications must be addressed to firstname.lastname@example.org and include “CPD2020-LOCODECISION-Data Analyst”” in the subject line. Paper applications must be handed at the Main Lobby Reception Desk of the Champalimaud Foundation in a closed envelope addressed to the HR & Fellows Office and identified with the abovementioned reference. Please include an email address at which to be contacted regarding your application.
The selected candidate must submit proof of her/his PhD or Doctoral Degree within 10 days following notification of the preliminary results. More information about Diplomas recognition may be found in the Euraxess portal.
All candidates who formalize their application incorrectly or who fail to provide the requirements imposed by this tender are excluded from admission. In case of doubt, the panel is entitled to request further documentation to support candidate statements.
Notification of Results: The highest scoring candidate will be notified by email or telephone. All other candidates will be also notified by email or telephone.
Prior hearing and deadline for final decision: After being notified, candidates will have 10 working days to present a claim by email. If no claim is received by the Champalimaud Foundation, the jury’s decision will become definitive.
The present call has the sole purpose of filling the indicated research position. This call may be cancelled at any time on or before the jury’s evaluation of all eligible candidates and the recruitment process shall be concluded on the day of the full execution of the employment contract between the Champalimaud Foundation and the selected candidate.
Non-discrimination and equal access policy: The Champalimaud Foundation actively promotes a policy of non-discrimination and equal access, so that no candidate can be privileged, benefited, harmed or deprived of any right, on basis of age, sex, sexual orientation, marital status, family status, economic situation, education, social origin or condition, genetic heritage, reduced working capacity, disability, chronic illness, nationality, race, territory of origin, language, religion, political or ideological convictions, and trade union membership.