Molecular simulations and modelling scientist (KTP Associate)
Newcastle, GB
Newcastle University
We are a world-class, Global Top 125 university dedicated to excellence, creativity, and innovation through our teaching and pioneering research.
Salary: £43,000 (plus substantial training budget) per annum
Newcastle University is a great place to work, with excellent benefits. We have a generous holiday package; plus the opportunity to buy more, great pension schemes and a number of health and wellbeing initiatives to support you.
Closing Date: 17 July 2025
The Role
RxCelerate and Newcastle University are offering an exciting opportunity to facilitate discovery of new innovative therapeutics, by developing and testing a method for identification of unique, short-lived states of proteins.
You will be part of a Knowledge Transfer Partnership (KTP) project which aims to deliver methodology to computationally predict and subsequently experimentally validate “druggable” states in disease-linked proteins.
RxCelerate is a leading drug discovery and development platform contract research company based in Cambridge, UK. They are driven by a mission to improve patients’ lives through scientific excellence and innovation. Rather than fitting to conventional drug discovery paradigms, RxCelerate specialise in bespoke experimental design with data-rich endpoints, maximising the chances of clinical success while reducing long-term costs. RxCelerate was founded in 2013 and employs around 100 people.
Based at RxCelerate you will be supported by an interdisciplinary team from Newcastle University, led by Dr Agnieszka K. Bronowska and Prof Wyatt Yue with expertise in Structural Biology and Computational Medicinal Chemistry. You will be also supported by a senior supervisor from RxCelerate.
Candidates should have a PhD in molecular simulations of biomolecular systems or related fields (e.g., computational biophysics, computational chemistry).
Benefits:
- Develop managerial skills and attend two residential managerial workshops (each of one-week duration)
- £4,000 personal training budget
- The opportunity to lead a project, develop project management skills and improve long-term career prospects
- Mentoring by a Knowledge Transfer Network Adviser
- Full access to university resources to complete the project
- Ability to work in a largely self-determined way, across the industry-academic partnership
- Opportunities to develop both technical understanding and commercial awareness
- The possibility of studying for a higher degree or undertaking professional development
The KTP Associate will be an employee of Newcastle University but will spend most of their working time at the company’s premises at The Dorothy Hodgkin Building, Babraham Research Campus, Babraham, Cambridge, Cambridgeshire, CB22 3FH and when required at Newcastle University. As part of your responsibilities, you will be required to travel to Newcastle approximately twice per year to conduct experimental validation.
The KTP Associate will follow RxCelerate’s working hours and holiday procedure. Your working week will be 37.5 hours. The shift pattern is Monday- Friday and there is flexibility within the core hours. Annual Leave applicable to this role is 25 days plus bank holidays.
Although the contract is fixed term for a duration of 2 years, more than 70% of KTP staff gain a permanent job offer by their KTP company.
For more information or informal enquiries, please contact Dr Agnieszka Bronowska at Agnieszka.Bronowska@newcastle.ac.uk or Prof Wyatt Yue at Wyatt.Yue@newcastle.ac.uk
For further details on the Faculty of Science, Agriculture & Engineering please visit our web page at: https://www.ncl.ac.uk/sage/
For further details about Knowledge Transfer Partnerships please visit the web page at: http://www.ktp-uk.org/
Key Tasks:
- Develop innovative enhanced sampling approaches (e.g., metadynamics, RAMD) to identify druggable states in therapeutically relevant proteins, and quantify interactions with small molecules.
- Design and implement an integrated, multiscale computational pipeline that combines atomistic/coarse-grained simulations, advanced sampling, and machine learning for predicting and analysing short-lived protein conformations.
- Enhance and automate workflows for reproducible simulations and structure-based modelling; document protocols and create user-friendly tools, tutorials, and scripts in line with scientific software best practices.
- Collaborate closely with structural biologists, medicinal chemists, and experimental biologists to validate predictions via wet-lab techniques (e.g., enzymatic assays, ligand-binding studies, and biophysical characterisation).
- Assist with analysis and interpretation of experimental data, supporting integration of computational and laboratory insights.
- Liaise regularly with both academic and industrial supervisors to align progress with project milestones and KTP deliverables.
- Translate academic research into commercially deployable tools and methodologies for early-stage drug discovery, contributing to RxCelerate’s bespoke design strategies.
- Contribute to innovation by staying informed of developments in molecular simulations, AI/ML, and virtual screening techniques; apply relevant methods to enhance pipeline capabilities.
- Prepare publications, case studies, technical documentation, and software releases; present outcomes at conferences and stakeholder events.
- Disseminate knowledge across the partnership through reports, meetings, mentoring, workshops, and outreach.
- Maintain clear and comprehensive project records including protocols, simulation workflows, software repositories, and data curation.
- Contribute to identification of intellectual property opportunities and support strategies for sustainability beyond the project lifespan.
Knowledge, Skills, and Experience:
Essential:
- Strong expertise in multiscale molecular simulations of proteins, integrating atomistic and coarse-grain approaches.
- Experience with simulation software (GROMACS, AMBER), molecular visualisation (UCSF Chimera, VMD), and scripting (Python, bash); competent with statistical tools (R, xmgrace).
- Proven track record in enhanced sampling techniques (e.g., metadynamics, RAMD) and familiarity with machine learning for biomolecular modelling.
- Demonstrable wet lab or assay experience (e.g., phosphatase assays, cytotoxicity assays, Western blot, HPLC) is also essential to enable effective collaboration with experimental teams.
- Ability to manage large computational datasets and develop reproducible workflows for protein-ligand analysis.
Desirable:
- Knowledge of structure-guided lead optimisation (e.g., SeeSAR, MOE)
- Proficiency in chemical space navigation and chemical space docking
- Published peer-reviewed work and contributions to open-access scientific software.
- Track record in writing software documentation and publication manuscripts.
- Experience in teaching, science communication and mentoring of junior researchers.
- Ability to manage large computational datasets and develop reproducible workflows for protein-ligand analysis.
- Proven ability to design and maintain computational workflows or scientific software for molecular simulations (e.g., trajectory analysis, back-mapping, binding pose optimisation).
- Experience with open-source contributions and/or web-based tools for MD simulation visualisation or parameter generation is advantageous.
Attributes and Behaviour:
- Personal motivation and drive.
- Excellent organisational and planning skills.
- Thrives in a project environment with the ability to work to tight deadlines. •
- The ability to work independently and collaboratively with colleagues.
- The ability to work autonomously and the confidence to lead.
- Strong interpersonal skills with the ability to communicate at all levels to different stakeholder groups in both academia and industry.
- Good attention to detail.
- Is a natural problem solver.
- Excellent verbal, written and presentation skills.
Qualifications / Experience-
- Candidates should have a PhD in molecular simulations of biomolecular systems or related fields (e.g., computational biophysics, computational chemistry).
To apply, please attach your CV and a cover letter that demonstrates how you meet the essential criteria for the position, as outlined in the Person Specification of the Job Description. Any requested additional documents required as part of your application, should be included within the same file as your cover letter. The total file size must not exceed 10MB
Newcastle University is a global University where everyone is treated with dignity and respect. As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution.
We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population.
At Newcastle University we hold a silver Athena Swan award in recognition of our good employment practices for the advancement of gender equality. We also hold a Race Equality Charter Bronze award in recognition of our work towards tackling race inequality in higher education REC. We are a Disability Confident employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme.
In addition, we are a member of the Euraxess initiative supporting researchers in Europe.
Requisition ID: 28253
Tags: Athena Biology Chemistry Drug discovery Engineering Industrial Machine Learning Open Source PhD Python R Research Statistics Teaching Testing
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