Assistant Professor Interview Questions

"My doctorate was on how soil moisture affects crop yield models, and during it I realised I liked explaining the work as much as doing it. I tutored two undergraduate courses in statistics, and in my final year I ran the lab sessions on my own. After that I did a two-year postdoc where I extended the models to rainfall data and published three papers, one as first author. I also co-supervised a master's student, which I really enjoyed. So I'm applying now because I have a research line I can run independently, real teaching experience to build on, and I want the chance to shape students over several years rather than a single project."

"I went through your faculty pages and the course list before applying. You have a strong group in machine learning and another in networks, but nobody working on security for embedded devices, which sits right between them and is my area. I could teach an elective on it and help the two groups collaborate on projects. I also noticed your department is trying to grow its master's research intake, and I've co-supervised master's theses before, so I'd be useful there from the first year. And honestly, I like that your students do a year-long capstone with industry partners. That's the kind of teaching I want to be part of."

"From the job description and talking to one of your faculty, I understand this post is teaching-heavy, with research expected but at a steadier pace than at a pure research institute. I'm comfortable with that. For me the two feed each other. My research gives me real examples to bring into class, and teaching the basics every year keeps my own thinking sharp. In practice I block two mornings a week for research and treat them like a class I can't cancel. During exam weeks that slips, and I accept it, but I make it up in the breaks. I'd rather be a good teacher who publishes steadily than chase numbers and neglect students."

"In my first semester as a lecturer I taught recursion to second-year students. I'd prepared forty slides and went straight through them. Halfway, I asked a question and got silence, and the next week's quiz showed most of them couldn't trace a simple recursive call. The problem was me. I'd explained it the way I understand it, not the way a beginner meets it. The next time I started with a physical example, stacking and unstacking boxes, then had them trace a small function on paper in pairs before I showed any slides. I cut the slides to about a dozen. The quiz results on that topic improved clearly the following year, and I now build a short hands-on task into every hard topic."

"After my first run of a research methods course, several students wrote in the end-of-term survey that the assignments felt disconnected and they didn't know how they'd be marked. A couple of comments were just about the timing of the class, which I couldn't change, so I set those aside. But the marking point was fair. I rewrote each assignment with a short rubric showing what a strong, adequate and weak answer looks like, and I linked each one to a stage of a single project they built across the term. I also added a quick anonymous check-in at week four instead of waiting until the end. The next year, complaints about unclear marking mostly disappeared, and the week-four check caught a pacing problem early."

"First I'd go through the scripts question by question. If most students failed the same two questions, that points at my teaching or the test design, not the students. I'd check whether those questions asked for something we hadn't practised. Then I'd ask the class, anonymously, what made the test hard: time, topics, or the question style. Based on that I'd reteach the weak topics with worked examples and add a practice set with feedback before the next assessment. If the test itself was unfair, I'd talk to the coordinator about how to handle it within the rules, rather than quietly scaling marks. I'd also let the coordinator know early, and I'd offer extra help sessions for students who scored lowest."

"I'd start with a short, ungraded diagnostic quiz in the first week so I know the spread instead of guessing. Then I'd be clear about the core every student must reach, and teach that core carefully. For students who are behind, I'd point them to specific catch-up material and run an optional help session, and I'd use short in-class checks so I spot who's slipping. For the students who find it easy, I'd give each problem set a harder extension question and sometimes an open-ended challenge linked to real research. In group work I'd mix levels on purpose, because the strong students learn a lot by explaining, and the others often understand a peer faster than me. The goal is that nobody's bored and nobody's lost."

"My philosophy is simple: students learn by doing and by getting feedback quickly, not by listening to me for an hour. So in my classes I talk for maybe fifteen minutes at a time, then give students a problem to try in pairs, and walk round to see where they get stuck. For example, in my database course, before I explain joins formally, I hand out two small printed tables and ask them to combine them by hand. They discover the idea, then I give it a name and the syntax. I also believe clear expectations are part of fairness, so every assignment has a rubric. The evidence I rely on is students' work improving across the term, not only their end-of-course ratings."

"I'd pick one idea I can teach properly in twenty minutes, not a whole chapter. I'd open by telling you what you'll be able to do by the end, then start with a real problem, say, why a bridge engineer cares about resonance. Next I'd explain the core concept with one clear worked example on the board, not a wall of slides. Around the twelve-minute mark I'd stop and ask the panel a question, the way I would ask students, to check understanding and show how I handle answers. Then a second, slightly harder example, and a two-minute summary linking to the next lecture. I'd watch the clock and cut the second example short before I'd overrun."

"With a big group I don't expect anyone to follow me talking for an hour straight, so I build the session in chunks of ten or fifteen minutes. After each chunk there's something everyone does: a quick poll on their phones, a question they discuss with the person next to them for two minutes, or a one-line answer they write down. Polls are useful because I see instantly whether the room got it, and I can reteach on the spot. I open with a real problem or a surprising result so they know why the topic matters. I also move away from the lectern and learn a few names each week. It won't be a seminar, but every student should have to think actively several times an hour."

"I'd want them to say two things: that I made a hard subject feel possible, and that I held them to a high standard because I believed they could meet it. That comes from my own undergraduate years. I had a professor in mathematics who was strict about deadlines and rigour, but who'd sit with anyone after class until they got it. I didn't love every assignment, but I left that course more capable and more confident. So in my own teaching I keep the bar high, and I make sure the help to reach it is always there: office hours, clear feedback, and practice before anything is graded. If they remember me as fair and demanding, I'll be happy."

"In my second postdoc year I sent a paper to a strong journal in my field and it came back rejected after review. Two reviewers said my sample was too small to support the main claim, and one said the related work missed a whole line of studies. I was annoyed for a day, then I reread the reviews and admitted they were mostly right. I collected another season of data, narrowed the claim to what the data actually supported, and rewrote the literature section. I also asked a senior colleague to read it cold before resubmitting elsewhere. It was accepted at another good journal with minor revisions. Since then I always get one outside reader before I submit anything."

"On a joint project during my postdoc, a colleague from another lab wanted to be first author on a paper where I'd designed the study and done most of the analysis. His lab had collected much of the data, so he had a real case. Instead of arguing over email, I suggested we sit down and list who did what against the authorship guidelines our field's main journals use: design, data, analysis, writing. Seeing it laid out, we agreed I'd be first author on this paper and he'd lead the follow-up using his new data, which we planned together. We still work together. Now I agree authorship order in writing at the start of any collaboration, and revisit it if roles change."

"I'd accept that the first year of new preparations is heavy for almost everyone, and set smaller research goals for that year rather than none. Concretely, I'd keep two half-days a week for research and treat them as fixed. I'd aim for things I can finish in those blocks: turning a thesis chapter into a paper, revising a paper under review, or writing a small grant application. I'd also lean on collaborators, so projects keep moving when I'm buried in marking, and bring a couple of undergraduate students into a small piece of the work. By mid-year I'd have an honest talk with the head about keeping the same courses next year, so the preparation time pays off twice."

"My core question is how to make water-quality sensing cheap enough for small towns to run themselves. In the first two years I'll finish two papers from my postdoc data and start a project on low-cost sensor calibration, which I can do with basic lab equipment and one or two final-year students. In my first year I'll also apply for a small early-career grant, and by year two or three a larger one to deploy sensors with a local municipal partner, and take on my first doctoral student. By year five I'd like a small group of three or four students, a steady run of journal papers, and at least one field deployment others can build on. It also links well with your environmental engineering group, which gives me natural collaborators."

"I start with the audience. If it's a method others in my exact area will use, I go to the main specialist journal. If it has broader interest, I'd aim wider. To judge quality I look at where the strongest papers in my field appear, who's on the editorial board, whether it's indexed in the major databases, and whether peer review is real. I also ask senior colleagues. I stay away from anything that sends unsolicited emails promising publication in a week for a fee, because that's the pattern of a predatory publisher, and a paper there can hurt more than help. I also think about timing: some journals take a year, so for a student who needs to graduate, a good conference may fit better in fields where conferences count."

"The paper I'm proudest of is about forecasting crop yields when rainfall records have gaps. Yield models expect daily rain data, but many small weather stations miss weeks at a time. It's a bit like guessing the end of a film with half the scenes missing. We showed that filling those gaps with soil moisture readings from satellites, instead of simple averages, made the forecasts clearly more reliable, especially in dry years, when farmers and planners need them most. I designed the gap-filling method and ran all the analysis. My co-authors supplied the field data and the crop model. Two other groups have since used the method, and it's the base my next project builds on."

"I co-supervised a master's student whose experiments kept failing, and by month five she'd stopped coming to our weekly meeting. When we finally sat down, it turned out she thought every failed run was her fault and was embarrassed to show me. The actual problem was a bad calibration in shared equipment. We fixed that together, but the bigger change was the way we worked. I asked her to send a short weekly note, three lines on what she tried, what happened and what she'd try next, whether it worked or not. That made failure normal and let me catch problems in days, not months. She submitted on time, and I've used that weekly note with every student since."

"I'd invite them to sit down and tell me exactly which part they think was marked unfairly. Their mention of the head doesn't bother me. Appealing is their right, and I'd rather they did it properly. Then I'd open the script and the rubric together and walk through the marks for that section. If I find I made a mistake, like missing a page or misreading an answer, I'd correct it and say so. If the mark stands, I'd explain what a full-mark answer would have included, so they leave knowing what to do next time. If they still disagree, I'd tell them how the formal re-evaluation works and give them the details. I'd also mention the conversation to the course coordinator so nobody is surprised."

"I'd stop and give them my full attention somewhere private, and I'd thank them for telling me. I wouldn't try to diagnose or fix it myself, because I'm not trained for that. I'd tell them the institution has a counselling service and offer to help them contact it right then, even walking over with them if they want. If anything they said suggested they might be at risk of harm, I'd follow the institution's safety procedure straight away, and I'd be honest that I can't keep that part secret. On the academic side, I'd explain that dropping out isn't the only option, and that extensions or a break in studies may be possible. Then I'd check in with them a week later."

"I start every student with a short written agreement: how often we meet, how fast I'll respond to drafts, and the milestones for the year. A new student gets a lot of structure. I give them a well-defined first problem that can produce a small result within a few months, because early success builds confidence, and I help with reading lists and methods. As they progress, I step back on purpose. By the final year I expect them to set the agenda for our meetings, defend their own choices, and draft papers with me mainly editing. Throughout, I give honest feedback quickly, and I ask about how they're doing, not just the results, because stress is often what stalls a thesis."

"During my postdoc I coordinated the department's weekly seminar series for two years. That meant inviting speakers, handling travel paperwork and making sure someone introduced each talk. It sounds small, but when I took it over, attendance had dropped because talks were announced late. I set up a term calendar a month ahead and asked each speaker for a two-line summary aimed at students, and attendance picked up. I've also reviewed papers for two journals and helped run an open day for school students. I learned that the department only works because people quietly do this kind of work, and I'm happy to take my share, whether that's timetabling, admissions or accreditation paperwork."

"I'd like to be the colleague people are glad to have on a committee, because I turn up prepared and finish what I take on. I'll do my share of the unglamorous work, exam invigilation, timetables, accreditation files, without needing to be chased. I'm also keen to collaborate. I'd happily co-teach a course, share my lab materials, or join a larger grant application if my skills fit. And I'll show up for the department's seminars and students' presentations, because a department feels alive when faculty attend each other's things. In my postdoc lab, the people I learned the most from were the ones who made time for others, and that's the kind of colleague I want to be."

"I wouldn't accuse anyone in class or by a quick email. First I'd compare the two pieces and the online source myself, marking the matching passages, because similarity software can flag quoted or common text. If it still looks like copying, I'd check the institution's academic integrity policy for the exact steps, since most places have a set process and a first offence is often handled differently from a repeat. Then I'd meet each student separately and ask them to talk me through their work. Often it becomes clear who wrote it and whether one shared it knowingly. I'd report it through the proper channel, apply the outcome the policy sets, and keep a written record. And I'd use it to remind the whole class how to cite."

"Because it's a draft sent to me, not a submitted thesis, I'd treat it first as a serious teaching moment. I'd sit down with the student, show the passages side by side with the sources, and say plainly that this is plagiarism even if they meant to cite later. Often it comes from poor note-taking, copying text into notes and losing track of where it came from. So I'd teach a better method: summarise in your own words with the source written next to it. I'd ask them to rewrite the chapter and I'd run the full thesis through the institution's similarity check before submission. If it happened again, or if I found it in work already submitted, I'd follow the formal integrity process. Protecting a student from that wouldn't protect them at all."

"I start with clear rules, written into each assignment: what help is allowed, including whether AI tools can be used for brainstorming or editing, and how to declare it. Then I design tasks that are hard to outsource. I use a dataset I collected, ask students to connect the work to a lab session we did together, or have them submit drafts and a short reflection on their choices, so I'm marking the process too. For bigger projects I add a five-minute oral check where they explain one decision, which quickly shows who did the work. I don't lean on AI detectors alone, because they can flag honest students wrongly. Good design protects honest students better than any detector."

"To me, outcome-based education means designing a course backwards. I first decide what a student should be able to do at the end, then plan teaching and assessment to get them there. A good outcome uses an observable verb. 'Understand sorting' is vague, but 'compare the running time of two sorting algorithms on a given input' can be taught and tested. I use Bloom's taxonomy to check the level, so a course doesn't sit only at remembering and explaining but also asks students to apply, analyse and design. I usually end up with five or six course outcomes, and I map each one to the programme outcomes, so it's clear what this course contributes to the degree."

"A total exam mark hides a lot. A student can pass while failing everything on one outcome. So I tag every question and assignment with the outcome it tests. After the course I look at results per outcome: say, whether at least two-thirds of the class scored above the set level on the items for outcome three. That's the direct measure. I add an indirect one, a short end-of-course survey asking students how confident they are on each outcome. If one outcome falls below the target the department has set, I don't just record it. I note why and change something, maybe more practice on that topic or a better-aligned assessment, and check next year whether it improved. That last step, closing the loop, is what accreditation reviews usually ask to see evidence of."

"I'd start by looking at where the elective sits: which year, what prerequisites students have, and what the programme is missing. Then I'd write five or so outcomes first, before any lecture topics, so the course has a spine. Say the elective is on embedded security: one outcome might be 'identify attack surfaces in a given device design'. From there I'd choose topics, a mix of lectures and labs, and assessments that test each outcome, including a small group project on a real device. I'd check the workload against the credit hours, share the draft with two colleagues and, if possible, someone from industry, then take it through the curriculum committee or board of studies for approval. After the first run I'd review outcome results and student feedback, and revise."

"First I'd find the right call. National research funders and many foundations run schemes meant for new or early-career researchers, and I'd read their priorities and past funded projects before writing anything. Then I'd shape the idea to fit, not the other way round. The proposal itself needs a clear problem, why it matters now, what's new about my approach, and preliminary results that show I can deliver. I'd write two or three specific aims with methods, a realistic timeline and the main risks with a fallback for each. For the budget, I'd justify every item against the work, whether it's a student's time, equipment or fieldwork. I'd involve the research office early for rules and deadlines, and ask a colleague who's won grants to review the draft. And I'd expect a rejection or two before a yes."