Collective dynamics of sleep in wild baboons
Supervisor: Dr. Meg Crofoot
We are seeking a doctoral student with a quantitative background and an interest in sleep physiology and behavioral ecology to join our ERC-funded team studying the social behavior and sleep of wild baboons. The researcher will be based at the Max Planck Institute of Animal Behavior and the University of Konstanz.
Research: All animals sleep. From honey bees to humans, animals spend from 12-83% of their lives in a behavioral state characterized by decreased responsiveness to environmental stimuli. Because insufficient sleep negatively impacts health, cognition, social functioning and, in extreme cases, can lead to death, the decisions animals make about when, where and how to sleep are important. While sleep is not typically thought of as a social behavior, when individuals sleep together, the choices they make and the tradeoffs they face are fundamentally shaped by the behavior of their group-mates and the collective dynamics that emerge from sleeping in groups.
How much does sleep quality vary among group-mates and what proportion of this variation is due to individual traits vs. the decisions individuals make about where and with whom to sleep? In deciding where to sleep, how do baboons weigh the trade-offs that define their sleep ‘micro-climate’, including exposure to the elements, risk of falling, availability of co-sleeping partners and relative safety from predators? And, by structuring baboons’ co-sleeping networks, do these socially contingent, collective decisions drive wake/sleep cycles at the group and population level?
By combining experimental and observational methods and building new tools to map the sleep patterns of wild baboons through space and time, we aim to answer these questions and better understand how social environments shape (and are shaped by) the sleep patterns of their members.
Qualifications: We are seeking candidates with an interest in developing and employing computational approaches to the study of sleep in the wild. This call is open to candidates from all scientific backgrounds with an MSc or equivalent, who can articulate how their interests and training prepare them for this position. Programming skills and an enthusiasm for tackling challenging analytical problems are essential. Applicants should ideally have prior experience with the analysis of bioelectrical signals (e.g. EEG, EMG, ECG), spatial, timeseries, or network data, and/or experience with machine learning. Strong communication skills, and the ability to work both independently and as part of an interdisciplinary team are also essential.
Funding: is confirmed for 4 years.
Research Statement Instructions: Applicants should include a research statement that addresses the following points:
- Describe your scientific background and research interests, and explain how they relate to the project.
- Describe a specific research question you would be interested to tackle using the types of data described in this paper:
Explain how you would go about addressing it, presenting explicit predictions and describing how you would use data to test those predictions
Questions: For further information regarding the position, please contact Meg Crofoot (firstname.lastname@example.org)
The University of Konstanz and the Max Planck Society are equal opportunity employers that are committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, gender, sexual orientation, gender identity, national origin, or disability. They seek to increase the number of women in those areas where they are underrepresented and therefore explicitly encourage women to apply (Equal opportunity). Persons with disabilities are explicitly encouraged to apply.
They will be given preference if appropriately qualified (contact +49 7531 88 4016).