Postdoctoral Fellowship in Neurocomputational Biomarkers

Switzerland, Basel-City, Basel

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At Roche, 80,000 people across 150 countries are pushing back the frontiers of healthcare. Working together, we’ve become one of the world’s leading research-focused healthcare groups. Our success is built on innovation, curiosity and diversity, and on seeing each other’s differences as an advantage. To innovate healthcare, Roche has ambitious plans to keep learning and growing – and is seeking people who have the same goals for themselves.

The Postdoctoral Fellowship in Neurocomputational Biomarkers is placed in the Biomarkers & Translational Technology group in order to facilitate the implementation and execution of novel computational analyses & assays in our biomarker discovery and clinical trial activities, including translational studies; to rigorously evaluate and broadly communicate the value of these approaches, both internally within our cross-functional department and externally at preeminent academic conferences; and to anticipate, create, identify, and manage our opportunities to deploy these approaches from computational neuroscience and computational cognitive neuroscience in our ongoing and future work.

The successful candidate is expected to have a strong background in neuroscience, with a major focus and significant experience in use of neurocomputational models to analyze cognitive neuroscience data. This skillset includes the use of neural networks, Bayesian methods, and/or model-free/-based reinforcement learning approaches to data from neuroimaging, eye-tracking, EEG/ERP, and/or cognitive, behavioral & neuropsychological assessments. The candidate should be well versed in multiple approaches to quantitative modeling of this data, and must demonstrate a keen awareness of both the limitations of these approaches as well as new opportunities.

Success in this role will involve maintaining cutting-edge scholarship by rapidly developing, reproducibly implementing, and clearly communicating (both internally and externally) complex statistical, mathematical and/or computational models as applied to neurobiological and neuropsychological data. The candidate will be expected to keep abreast of new developments in relevant biomarker modalities and computational approaches in the literature; to communicate and disseminate these advancements as appropriate within and beyond the group; and to rigorously evaluate the potential of these techniques for experimental medicine and clinical trials.

The candidate should further be able to maintain the infrastructure necessary for these analyses, independently conduct these analyses, interpret and communicate complex results to both domain-area experts as well as the more diverse scientific community. Good oral and written communication skills, deep knowledge of advanced computational methods, and experience with diverse biomarker modalities (in particular, in the context of pharmacological research) are therefore essential skills for this role.

Primary Accountabilities and Responsibilities                     

  • Stay abreast of emerging computational techniques within neuroscience, via regular review of peer-reviewed papers, preprints, attending relevant conferences, and membership in relevant working groups/consortia;
  • Proactively identifying opportunities for powerful modeling of various data types (EEG, fMRI, eyetracking, behavior) by seeking out discussions with our internal experts;
  • Using Bayesian and/or neural network methods for biomarker-based approaches to population stratification, to response or prognosis prediction, to establishing target engagement or pharmacodynamic activity, or to providing an early signal of efficacy, in the context of clinical trials;
  • Communicating the results of these analyses in the form of regular internal updates, periodic internal and external presentations and posters, and peer-reviewed publications at landmark achievements
  • Excellent timeline management, including providing clear timelines associated with these analyses, proactively identifying timeline risks (e.g., due to model nonconvergence), and taking efforts to mitigate these risks
  • Fairly and critically evaluate key precedents to your work, both internal and external, including a rigorous understanding of the risks of experimenter degrees of freedom, the importance of pre-registration, and the importance of error rate control in iterated research & development efforts
  • Contribute to the intellectual atmosphere of the group by going beyond your “comfort zone” in regular discussions and scientific dialogue, engaging diverse experts on their own research territory with your quantitative modeling perspective

Experience, Skills and Knowledge:

  • Experience in applying multiple computational techniques, preferably from both frequentist, Bayesian and neural network/connectionist frameworks, to neuroscientific problems
  • Expertise in Matlab, R and/or Python
  • Excellent oral and written communication skills
  • Strong presentation skills
  • Ensures communication is two-way; responds and acts on feedback.
  • Establishes & maintains good working relationships and is co-operative.
  • Familiarity with pre-registration tools including or is a plus


  • Minimum: PhD or equivalent
  • High-profile publications in this area are a plus

You have very good interpersonal and communication skills, are able to build good working relationships, and are an outstanding teammate. Your experience and investigative attitude allow you to work independently, to design, perform, and interpret experiments, and to embark on new scientific methodologies.

When does it start? The start date of this fellowship is 1st November, or on availability. Please clearly indicate your preferred starting date on your motivation letter. All applications always need to include a CV, motivation letter, a publication list and a certificate of your PhD (if already available).

Do you know what Roche stands for? Roche embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.

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