Postdoctoral Fellow in Scientific Machine Learning – Fröhlich lab

Postdoctoral Fellow in Scientific Machine Learning – Fröhlich lab
Reporting to: Fabian Fröhlich, Group Leader
Contact term: This is a full-time, fixed term (4 years) position on Crick terms and conditions of employment.
Closing date and time: open until filled
The Research Group
The Fröhlich lab builds computational models to unravel the regulatory principles underlying the dynamics of intracellular signalling. We build these models by blending techniques from mathematical modelling and machine learning. More details about the group and our research interests can be found on the lab’s webpage www.frohlichlab.com
The successful candidate will join a growing, multi-disciplinary team of scientist with the opportunity to contribute own ideas and help shape the research profile of the lab. Currently, there is one PhD student and one Postdoc in the team, who have backgrounds in structural biology, systems biology, electrical engineering, and chemical nanotechnology. Research projects will be supported by a vibrant, multi-disciplinary scientific community at the Crick, with ample opportunities for internal and external collaborations. Moreover, the candidate will have access to state-of-the-art core facilities at the Crick, including the High-Performance-Computing platform, as well as structured career development and rich networking opportunities.
The Role
Multiple research avenues are pursued within our laboratory, offering the successful candidate the autonomy to develop and lead their own independent research projects aligned with the lab’s focus. Prospective projects encompass:
Unravelling emergent dynamical laws from complex mathematical models of protein-protein interactions. Employing symbolic regression techniques on simulated data enables the extraction of simplified rate laws, integral for constructing models of multi-component signalling pathways. These models could then be used investigate signal transduction heterogeneity resulting from fluctuations in protein levels or to design synthetic multicomponent signalling cascades de novo.
Crafting dynamic, multi-pathway signal transduction models by integrating prior knowledge networks (PKNs) with phosphoproteomic data. Transforming PKNs, which consolidate knowledge graphs, pathway databases, and protein structure information, into simulatable models allows for validation against dynamic multi-condition proteomics datasets. The primary objective is to discern the regulatory ‘grammar’ governing phosphorylation dynamics, elucidating molecular mechanisms or cellular processes that drive signalling dynamics.
Deciphering cell cycle dynamics using pseudo-time embeddings derived from snapshot mass cytometry data. Leveraging low-dimensional embeddings to temporally order unsynchronized cell populations based on cell cycle marker expression facilitates the learning of dynamic models from static snapshot data. Leveraging mass cytometry datasets spanning diverse experimental conditions – including growth factor stimulation, genetic modifications, and small molecule drug interventions – aims to unveil the dependency of cell cycle dynamics on upstream signalling.
The post holder will be responsible for:
Leading and developing specific research projects
Developing and maintaining computational tools
Applying methods to biological data and interpreting results
Collaborating with national and international partners
Presenting work at lab meetings as well as national and international meetings
Publishing scientific results
Assisting in training graduate students and other members of the laboratory
Key experience and competencies
The post holder should embody and demonstrate our core Crick values:
Bold; Open; Collegial, in addition to the following:
Essential
PhD in a relevant field or in the final stages of PhD submission
Good knowledge and experience in coding (Python/Julia/C or similar languages)
Technical expertise in mathematical modelling and/or machine learning
An interest in applying computational methods to biological problems
A demonstrated ability to generate and pursue independent research ideas
Excellent communication skills, written and verbal as evidenced by publications, preprints and/or conference presentations
Cross-disciplinary mindset, collaborative attitude, and teamwork experience
Dedication to reproducible research and open science
A cover letter that is tailored to the lab and the position
Desirable
Foundational knowledge in Cell Biology, Biochemistry and/or Systems Biology
Foundational knowledge in Mathematics, Physics, Statistics and/or Data Science
Background in numerical methods for optimization and solving differential equation models
Familiarity with modern software development practices and high-performance computing
Good command of a machine learning framework (jax/pytorch or similar)
Experience working in interdisciplinary environments
Note that the ideal candidate is not expected to have all desirable skills, but this listing is intended to give you some guidance of what experiences to highlight in your cover letter.
About Us
At the Crick, we conduct research at the forefront of biomedical research. We combine rigour with an open and collaborative culture, and are outward-looking, reflecting our status as a partnership of six organisations aiming to pool knowledge, ideas and resources.
We have a wide research portfolio with no divisions or departments, bringing biomedical researchers together with clinicians, physical scientists and applied scientists from our pharmaceutical partners.
We aim to attract the most talented researchers and support them to tackle innovative research questions. Our science technology platforms provide our researchers with access to state-of-the-art technology and expertise.
We provide an excellent learning environment with dedicated education programmes in public engagement with science, education and personal development, and a postdoc training programme that prepares scientists for leadership roles in science.
If you are interested in applying for this role, please apply via our website.
All offers of employment are subject to successful security screening and continuous eligibility to work in the United Kingdom.
If you require a visa to work in the UK we will help support your application should you be successful
Equality, Diversity & Inclusion
We welcome applications from all backgrounds. We are committed to providing equal employment opportunities, regardless of ethnicity, nationality, gender, sexual orientation, gender identity, religion, pregnancy, age, disability, or civil partnership, marital or family status. We particularly welcome applications from people who are Minority Ethnic as they are currently underrepresented in the Crick at this level.
Diversity is essential to excellence in scientific endeavour. It increases breadth and perspective, leading to more innovation and creativity. We want the Crick to be a place where everyone feels valued and where diversity is celebrated and seen as part of the foundation for our Institute’s success.
The Crick is committed to creating equality of opportunity and promoting diversity and inclusivity. We all share in the responsibility to actively promote dignity, respect, inclusivity and equal treatment and it is our aim to ensure that these principles are reflected and implemented in all strategies, policies and practices.
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