Research Fellow

Heriot-Watt University
Midlothian
10 months ago
Applications closed

Related Jobs

View all jobs

Research Fellow in Genomic Data Science

Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference

Research Fellow in Genomic Data Science

InTent Internship Programme 2025 (#IIP): Paid Summer Placement/Internship for Undergraduate’s (Bachelor’s) or Graduate’s (Master’s) Students in Agricultural Sciences, Environmental Sciences, Data Science (3months) at University of

Software Engineer

Senior Data Scientist London, England

Directorate: School of Engineering & Physical Sciences

Salary: Grade 8 (£45,585-£56,021)

Contract Type:Full Time (1FTE), Fixed Term (36 Months)

Detailed Description

Applicants should hold a PhD in Chemical Engineering, Biochemistry, Chemistry or a related subject and have substantial experience in molecular modelling with either dynamics simulations and/or molecular based equations of state. Applicants will have experience with regular use of/contribution to GitHub or similar code repositories and be proficient in Python.

Applicants are expected to have excellent verbal and written communication skills, with a demonstrated ability to write refereed journal articles and present work at scientific/engineering conferences. 

These full-time positions based in the School of Engineering and Physical Sciences at Heriot Watt University are funded for up to 3 years in the first instance. Post holders will be expected to develop independent research proposals (with support from Prof McCabe and Prof Cummings and others in the University including the university’s Research Engagement Directorate).

The intention is for postholders to transition to full members of the university’s academic staff (nominally Assistant Professor in the first instance). This will be dependent on achieving clear goals that will be set at the start of the appointment period in consultation with the corresponding Head of Research Institute and approved by Executive Dean. The goals will include publications and explicit contributions to grant income winnings. 

The posts are primarily research-focused, however an appropriate contribution to the support of teaching in the School of Engineering and Physical Sciences will be required, and indeed this is an important part of development in order to transition into a member of the Academic Staff. 

This position is graded on the University’s Grade 8 scale, for which the salary range is £45,585-£56,021 per annum. The actual starting salary offered will be based on qualifications and relevant skills acquired. 

Key Duties and Responsibilities 

Manage projects in terms of the simulation methodology that is most applicable, running simulations and curating the data. Manage codes via a repository (GitHub) and to maintain, document and publicize that code. Be an innovator, by developing and expanding projects over time, and presenting novel ideas to other team members for adoption.  Develop research proposals including for an Independent Fellowship  Contribute to supporting teaching within the School of Engineering and Physical Sciences.  Collaborate in and/or lead in the preparation of scientific reports and journal articles and present papers, posters and talks. Use and advise on the most effective usage of Tier 2 and Tier 1 national computing resources as suitable for the project. Act as a source of information and advice to other members of the group on scientific protocols and simulation techniques. Represent the research group at meetings and conferences, either with other members of the group or alone. Mentor junior members of the group (PhD graduate students or undergraduate project research students).

Please note that this job description is not exhaustive, and the role holder may be required to undertake other relevant duties commensurate with the grading of the post. Activities may be subject to amendment over time as the role develops and/or priorities and requirements evolve.

Education, Qualifications and Experience

Essential Criteria 

Hold a PhD or be near completion of a PhD in Chemical Engineering, Chemistry, Biochemistry or a related subject with a strong computational component. Have strong evidence of outputs from research, such as publications in high quality peer-reviewed journals. Possess excellent communication skills, including leading writing of journal articles and presenting results internally and externally. Show an ability to work supportively in a laboratory environment.

Desirable Criteria 

Familiarity with GROMACS, HOOMD, LAMMPS and/or SAFT-based equations of state.  Experience in machine learning methods.  Experience with using and contributing to GitHub or similar code repository. Demonstrated proficiency in Python  Proven HPC skills 

About our Team

The School of Engineering & Physical Sciences has a strong international research reputation and close connection with the professional and industrial world of science, engineering and technology.

Our research ranges from fundamental sciences through to engineering applications, all of which are supported by strong external funding. We have around 150 full-time academic staff who drive this research activity and are based in 5 research institutes: the Institute of Chemical Sciences, the Institute of Photonics & Quantum Sciences, the Institute of Mechanical, Process & Energy Engineering, the Institute of Sensors, Signals & Systems and the Institute of Biological Chemistry, BioPhysics & BioEngineering. In REF2021 Physics scored top in the UK for world-leading research outputs, whilst in Engineering our joint submission with the University of Edinburgh was ranked 1st in Scotland and 3rd in the UK for quality and breadth of research based upon the standard Research Power formula as used by the Times Higher Education. 

We deliver teaching across six programmes: Chemistry; Physics; Electrical, Electronic & Computer Engineering; Chemical & Process Engineering; Mechanical Engineering and Brewing & Distilling, and will soon add Aerospace Engineering to our undergraduate programme portfolio. 

The School of Engineering & Physical Sciences has received the Bronze Award from the Athena SWAN Charter recognising excellence in championing employment of women in the fields of science and technology, engineering and mathematics. 

Heriot-Watt University has five campuses: three in the UK (Edinburgh, Scottish Borders and Orkney), one in Dubai and one in Malaysia. The University offers a highly distinctive range of degree programmes in the specialist areas of science, engineering, design, business and languages. With a history dating back to 1821, Heriot-Watt University has established a reputation for world-class teaching and practical, leading-edge research, which has made it one of the top UK universities for business and industry. We connect with industry at every level and develop programmes to match their needs – so employers get work-ready industry-fit graduates. 

Heriot-Watt is also Scotland's most international university, boasting the largest international student cohort.

We have an established set of values that help us to nurture innovation and leadership, and show our commitment to continuous improvement and development in all our activities. 

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.