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PhD Candidate Computational Research on Neurophysiological Data

Do you want to be part of a multidisciplinary team investigating the (synchronization) mechanisms of within the neuronal network of the circadian clock in mammals? We are looking for a PhD candidate who will use mathematical and computational tools to investigate the network properties of the SCN. Are you the candidate we are looking for?

ongeveer een maand geleden


Albinusdreef, Leiden, Zuid-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
36 uur
€ 2422 - € 3103 per maand


Due to a significant increase in the use of artificial light in our 24h economy, the biological clocks of all living organisms, including humans, are severely disrupted. Many severe health disorders are consequences of clock disruption such as diabetes, sleep/mood disorders, cardiovascular disease, and immune dysfunction. The central timekeeper in mammals controlling the daily rhythms in basically all physiological functions and behavior, is the suprachiasmatic nucleus (SCN). The mechanisms by which light disrupts integrity of the SCN has been well investigated in nocturnal species. In contrast, mechanisms of clock disruption in humans and other diurnal (day-active) species remain poorly defined. The network in which the neurons are organized in the SCN gives rise to emergent properties that are not possible at the single-cell level. The SCN’s ability to adjust its activity to match seasonal changes in day length is dependent upon a network of oscillators with intrinsic coupling plasticity. Moreover, both aging and disease can reduce coupling strength, thereby affecting the function of the circadian system. Mathematical and computational techniques are powerful tools for revealing network properties that are not readily visible from the experimental data. We will use a number of powerful mathematical and computational tools to assess these “hidden” properties in the experimental datasets. Examples of datasets are time series of multi- and single unit neuronal activity, clock gene expression, locomotor activity, and possibly other sources of data. Examples of the mathematical and computational tools are Detrended Fluctuation Analysis, Granger Causility, algebraic and spectral graph theory, network inference and inverse-problem analyses, community detection in structural and correlation-based networks, time-series non-linear analyses.

Summary of the required skills

·        You hold a master’s degree in computational biology, computer science, electrical engineering, statistics, or physics

·        You have demonstrated programming skills for data analysis

·        You have affinity with neuroscience, biology and machine learning techniques

·        You will translate your results into publications

·        You are very much into the subject of the consequences of disruptions of the biological clock


You are highly motivated and have a strong background in computer science and/or mathematics, and specifically, experience with analyzing high-dimensional datasets is preferred. Some acquaintance with biology and/or neuroscience is ideal, as is the ability to adapt quickly and be part of a cross-functional team. You have a master’s degree in computational biology, computer science, electrical engineering, statistics, or physics, obtained within the last five years. You should have demonstrated programming abilities, and preferably have proficiency in Matlab or R. You should have affinity with, and preferably have knowledge about machine learning techniques, time series analysis, and/or dynamical differential equations. In addition, you are motivated to translate the developed research into publications. Finally, you are possess excellent communicative skills in English.


You will be employed on the basis of a 36-hour week. Appointment is for a maximum of four years, to be completed with a doctoral thesis. Your salary is € 2,422 gross per month in the first year, amounting to € 3,103 in the fourth year (scale PhD students, CLA UMC).

Additional information

Your career at the LUMC

The LUMC offers opportunities to maintain and develop your knowledge and skills. We offer internal courses and in-service training to help you with your personal development. We also offer services for mobility and career advice. You will be trained to become a computational neuroscientist who will be able to communicate with both worlds and can detect new neuronal principles in data sets as well as suggest new experimental designs to facilitate the use of computational techniques. Some skills we will help you train in include biological knowledge, scientific project management, oral presentations and scientific publications in peer reviewed journals.

Contact: Jos Rohling, senior researcher, Department of Cell and Chemical Biology

Telephone: +31(0)71 526 97 62.